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Pathogens
Volume 13
Issue 2
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Pathogens, Volume 13, Issue 2 (February 2024) – 85 articles

Cover Story (view full-size image): Influenza types A and B can cause big problems with seasonal outbreaks and worldwide pandemics. People can catch two main kinds of flu: A (IAV) and B (IBV). IBV accounts for about 25% of all yearly flu cases. IBV evolved into B/Yamagata and B/Victoria lineages in the mid-1980s. In 2013, the CDC suggested making quadrivalent vaccines that cover both IBV lineages. In this study, we included six computationally optimized immunogens (IBV-Epi) to protect against IBV infection. Our immune data show that IBV-Epi induces strong B and T cell responses against both lineages. We performed challenges in mice, and IBV-Epi outperformed the commercial vaccine, Fluzone. These results indicate that Epigraph immunogens are superior in providing solid protection against a diverse set of IBV. View this paper
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4 pages, 161 KiB  
Editorial
Bacterial Infections: Surveillance, Prevention and Control
by Anna Maria Spagnolo
Pathogens 2024, 13(2), 181; https://doi.org/10.3390/pathogens13020181 - 17 Feb 2024
Viewed by 1669
Abstract
Bacteria play a vital role in maintaining human health, but they may also be responsible for many different serious infections and diseases [...] Full article
(This article belongs to the Special Issue Bacterial Infections: Surveillance, Prevention and Control)
15 pages, 691 KiB  
Review
Updated Clinical Guidelines on the Management of Hepatitis C Infection in Children
by Chaowapong Jarasvaraparn, Christopher Hartley and Wikrom Karnsakul
Pathogens 2024, 13(2), 180; https://doi.org/10.3390/pathogens13020180 - 16 Feb 2024
Cited by 2 | Viewed by 2053
Abstract
Children represent only a small proportion of those infected with the hepatitis C virus (HCV) compared to adults. Nevertheless, a substantial number of children have chronic HCV infection and are at risk of complications including cirrhosis, portal hypertension, hepatic decompensation with hepatic encephalopathy, [...] Read more.
Children represent only a small proportion of those infected with the hepatitis C virus (HCV) compared to adults. Nevertheless, a substantial number of children have chronic HCV infection and are at risk of complications including cirrhosis, portal hypertension, hepatic decompensation with hepatic encephalopathy, and hepatocellular carcinoma in adulthood. The overall prevalence of the HCV in children was estimated to be 0.87% worldwide. The HCV spreads through the blood. Children born to women with chronic hepatitis C should be evaluated and tested for HCV due to the known risk of infection. The course of treatment for hepatitis C depends on the type of HCV. Currently, there are two pan-genotype HCV treatments (Glecaprevir/pibrentasvir and Sofosbuvir/velpatasvir) for children. We aim to review the updated clinical guidelines on the management of HCV infection in children, including screening, diagnosis, and long-term monitoring, as well as currently published clinical trials and ongoing research on direct acting antiviral hepatitis C treatment in children. Full article
(This article belongs to the Special Issue Hepatitis C Virus Infection in Humans and Animals: Pathogenesis, Prevention and Treatment)
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<p>Diagnosis of HCV infection in perinatally HCV-exposed infants [<a href="#B24-pathogens-13-00180" class="html-bibr">24</a>].</p> Full article ">
16 pages, 1773 KiB  
Article
Exposure to Brucella Species, Coxiella burnetii, and Trichinella Species in Recently Imported Camels from Sudan to Egypt: Possible Threats to Animal and Human Health
by Ragab M. Fereig, Amira M. Mazeed, Ashraf A. Abd El Tawab, Mohamed El-Diasty, Ahmed Elsayed, Raafat M. Shaapan, Abdelbaset E. Abdelbaset, Caroline F. Frey, Bader S. Alawfi, Sarah A. Altwaim, Azzah S. Alharbi and Gamal Wareth
Pathogens 2024, 13(2), 179; https://doi.org/10.3390/pathogens13020179 - 16 Feb 2024
Cited by 1 | Viewed by 1525
Abstract
Brucellosis and coxiellosis/Q fever are bacterial infections caused by Brucella species and Coxiella burnetii, respectively; camels are highly susceptible to both pathogens. Trichinellosis is a parasitic infection caused by various Trichinella nematode species. Reportedly, camels are susceptible to experimental infection with Trichinella [...] Read more.
Brucellosis and coxiellosis/Q fever are bacterial infections caused by Brucella species and Coxiella burnetii, respectively; camels are highly susceptible to both pathogens. Trichinellosis is a parasitic infection caused by various Trichinella nematode species. Reportedly, camels are susceptible to experimental infection with Trichinella spp., but information on this potential host species is scarce. All three infections are of zoonotic nature and thus of great public health concern. The current study aimed to determine antibodies against the three pathogens in recently imported camels (n = 491) from Sudan at the two main ports for the entrance of camels into southern Egypt using commercial indirect ELISAs. Samples were collected in two sampling periods. The seropositivity rates of Brucella spp., C. burnetii, and Trichinella spp. were 3.5%, 4.3%, and 2.4%, respectively. Mixed seropositivity was found in 1% for Brucella spp. and C. burnetii. Marked differences were found between the two study sites and the two sampling periods for Brucella. A higher rate of seropositivity was recorded in the Red Sea/older samples that were collected between 2015 and 2016 (4.3%, 17/391; odds ratio = 9.4; p < 0.030) than in those collected in Aswan/recent samples that were collected between 2018 and 2021 (0/100). Concerning C. burnetii, samples collected during November and December 2015 had a significantly higher positivity rate than the other samples (13%, 13/100; OD = 4.8; p < 0.016). The same effect was observed for antibodies to Trichinella spp., with samples collected during November and December 2015 showing a higher positivity rate than the other samples (7%, 7/100; OD = 10.9; p < 0.001). This study provides valuable information on the seroprevalence of Brucella spp. and additional novel information on C. burnetii and Trichinella spp. in recently imported camels kept in quarantine before delivery to other Egyptian regions. This knowledge can be utilized to reduce health hazards and financial burdens attributable to brucellosis, Q fever, and trichinellosis in animals and humans in Egypt. Full article
(This article belongs to the Special Issue Epidemiology and Outcomes Research in Infectious Diseases)
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<p>Map of Egypt showing the collection sites of camel sera from southern Egypt. The red symbol refers to the Shalateen quarantine area in the Red Sea governorate, while the bluish symbol indicates the place of Abu Simbel quarantine in the Aswan governorate.</p> Full article ">Figure 2
<p>Seroprevalence of <span class="html-italic">Brucella species</span>, <span class="html-italic">Coxiella burnetii</span>, <span class="html-italic">Trichinella</span> spp., and mixed infections in tested camels. Various indirect ELISAs were used for testing the camel (n = 491) as confirmatory tests for detection of specific antibodies against selected pathogens. RBT, Rose Bengal test; BAPAT, Buffered acidified plate antigen test. Values above the bars refer to the estimated seroprevalence rates.</p> Full article ">Figure 3
<p>Evaluation of seroreactivity levels among positive and negative samples against selected pathogens. Antibody levels indicated in % of inhibition of positive and negative test samples and control negative and positive samples provided in the kit were compared. (<b>A</b>) % of inhibition among field and control samples tested by <span class="html-italic">Brucella</span> ELISA kit. (<b>B</b>) % of inhibition among field and control samples tested by <span class="html-italic">Coxiella burnetii</span> ELISA kit. (<b>C</b>) % of inhibition among field samples and control samples tested by <span class="html-italic">Trichinella</span> spp. ELISA kit. The different letters above the bars in the graphs indicate the statistically significant differences among groups (one-way ANOVA with Tukey–Kramer post hoc analysis, <span class="html-italic">p</span> &lt; 0.05). NC, negative controls; PC, positive controls; NS, negative samples; PS, positive samples; SPS, strong positive samples. Samples were identified as negative, positive, or strong positive based on % of inhibition of the manufacturer’s instructions for each kit.</p> Full article ">Figure 4
<p>Factors influencing the estimated seroprevalence of <span class="html-italic">Brucella</span> species in camels. The effect of collection sites and periods were investigated using univariate logistic regression to identify the risk factors for brucellosis. (<b>A</b>) Samples collected at Shalateen (Red Sea governorate, 17/391) showed a significantly higher seropositive rate than those collected at Abu Simbel (Aswan governorate, 0/100). (<b>B</b>) In addition, the samples from different collection periods exhibited variable seropositive rates in a statistically significant manner. Compared to samples collected during September 2018–March 2021 (Reference group, 0/100), the seroprevalence was significantly higher in samples collected during November 2015–December 2015 (6/100) and those during February 2016–March 2016 (11/291), but in a non-significant manner. The result is significant at <span class="html-italic">p</span> &lt; 0.05, as calculated by Fisher’s exact test. Values above the bars refer to the estimated seroprevalence rates.</p> Full article ">Figure 5
<p>Factors influencing the estimated seroprevalence of <span class="html-italic">Coxiella burnetii</span> in camels. The effect of collection sites and periods were investigated using univariate logistic regression to identify the risk factors for brucellosis. (<b>A</b>) Samples collected at Shalateen (Red Sea governorate, 18/391) showed a similar seropositive rate to those collected at Abu Simbel (Aswan governorate, 3/100). (<b>B</b>) Compared to samples collected during September 2018–March 2021 (Reference group, 3/100), the seroprevalence was significantly higher in samples collected during November 2015–December 2015 (13/100), but it was not different than those collected during February 2016–March 2016 (5/291). The result is significant at <span class="html-italic">p</span> &lt; 0.05, as calculated by Fisher’s exact test. Values above the bars refer to the estimated seroprevalence rates.</p> Full article ">Figure 6
<p>Factors influencing the estimated seroprevalence of <span class="html-italic">Trichinella</span> species in camels. The effect of collection sites and periods were investigated using univariate logistic regression to identify the risk factors for brucellosis. (<b>A</b>) Samples collected at Shalateen (Red Sea governorate, 9/391) showed a similar seropositive rate to those collected at Abu Simbel (Aswan governorate, 3/100). (<b>B</b>) Comparing to samples collected during February 2016–March 2016 (5/291) (Reference group, 2/291), the seroprevalence was significantly higher in samples collected during November 2015–December 2015 (7/100), but it was not different than those collected during September 2018–March 2021 (3/100). The result is significant at <span class="html-italic">p</span> &lt; 0.05, as calculated by Fisher’s exact test. Values above the bars refer to the estimated seroprevalence rates.</p> Full article ">
19 pages, 10752 KiB  
Article
Genetic Variability of Bovine Leukemia Virus: Evidence of Dual Infection, Recombination and Quasi-Species
by Aneta Pluta, Marzena Rola-Łuszczak, Federico G. Hoffmann, Irina Donnik, Maxim Petropavlovskiy and Jacek Kuźmak
Pathogens 2024, 13(2), 178; https://doi.org/10.3390/pathogens13020178 - 15 Feb 2024
Viewed by 1547
Abstract
We have characterized the intrahost genetic variation in the bovine leukemia virus (BLV) by examining 16 BLV isolates originating from the Western Siberia–Tyumen and South Ural–Chelyabinsk regions of Russia. Our research focused on determining the genetic composition of an 804 bp fragment of [...] Read more.
We have characterized the intrahost genetic variation in the bovine leukemia virus (BLV) by examining 16 BLV isolates originating from the Western Siberia–Tyumen and South Ural–Chelyabinsk regions of Russia. Our research focused on determining the genetic composition of an 804 bp fragment of the BLV env gene, encoding for the entire gp51 protein. The results provide the first indication of the quasi-species genetic nature of BLV infection and its relevance for genome-level variation. Furthermore, this is the first phylogenetic evidence for the existence of a dual infection with BLV strains belonging to different genotypes within the same host: G4 and G7. We identified eight cases of recombination between these two BLV genotypes. The detection of quasi-species with cases of dual infection and recombination indicated a higher potential of BLV for genetic variability at the intra-host level than was previously considered. Full article
(This article belongs to the Collection Bovine Leukemia Virus Infection)
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<p>Map with locations of sample collection. Maps showing the location of the study area in the Tyumen (Koktiul) and Chelyabinsk (Koelga) regions of the West Siberian Plain (the Russian Federation).</p> Full article ">Figure 2
<p>Heatmap of pairwise genetic distances (%) calculated using the alignment of 20 clones from 1S isolate. The numbers show the proportion of nucleotide substitutions in the 804 bp fragment of <span class="html-italic">env</span> gene.</p> Full article ">Figure 3
<p>Heatmap of pairwise genetic distances (%) calculated using the alignment of 20 clones from 4T isolate. The numbers show the proportion of nucleotide substitutions in the 804 bp fragment of <span class="html-italic">env</span> gene.</p> Full article ">Figure 4
<p>Bayesian phylogenetic tree based on 804 bp of <span class="html-italic">env</span> gene sequences of BLV isolates. The tree was midpoint rooted, indicated in the right site of tree by G1–G10 and G12. Numbers on nodes indicate posterior probabilities. The 83 sequences used in this analysis derived from 20 clones from each 1S (orange) and 4T (violet) isolate, 14 remaining isolates (shaded in yellow) and 27 reference data (black). The G11 genotype was not included in the phylogenetic analysis due to the lack of full gp51 length sequences existing in available databases.</p> Full article ">Figure 5
<p>Phylogenetic network inferred using the NeighborNet model for 20 sequences representative for clones of the isolate 1S, analyzed with 14 sequences from the Tyumen and Chelyabinsk regions and 27 reference BLV sequences, available from GenBank. Sequences classified as genotypes 4 and 7 are ticked on the edge of the network. The putative recombinants 1S-c1, 1S-c2, 1S-c9 and 1S-c11 are shaded in blue. The fit index for the split network was 98.3%. A fit index above 90% is considered as robust.</p> Full article ">Figure 6
<p>Phylogenetic network inferred using the NeighborNet model for 20 sequences representative for clones of the isolate 4T, analyzed with 14 sequences from the Tyumen and Chelyabinsk regions and 27 reference BLV sequences, available from GenBank. Sequences classified as genotypes 4 and 7 are ticked on the edge of the network. The putative recombinants 4T-c1, 4T-c19, 4T-c20, 4T-c21 are shaded in blue. The fit index for the split network was 96.5%. A fit index above 90% is considered as robust.</p> Full article ">Figure 7
<p>Bayesian phylogenetic trees from clone sequences from isolate 1S. (<b>A</b>) Color representation of recombinant sequences with portions similar to genotype G4 in red and portions similar to genotype G7 in green. Horizontal brown lines indicate the location of inferred recombination breakpoints. Labeled rectangles in the upper part of figure (yellow, orange) refer to the coding sequences of antigenic determinants. Epitopes A, B, B′, D, D′, E, E′ (linear), F, G, H (conformational), ND1,2,3–neutralization domain, CD4+, CD8+, N5, N11 and N12–T cell epitopes, Zbp-Zinc-binding peptide, GYDP strong turn, THMR–transmembrane hydrophobic region, CXXC sequence in disulfide bond. (<b>B</b>–<b>D</b>) trees are based on three separate non-recombining regions of <span class="html-italic">env</span> gene, identified via the Phylo-HMM algorithm and referred to as the 5′ terminus 1–240 bp, 241–542 bp, and 543–804 bp regions, respectively. Label names are shown in black for G1–G3, G5, G6, G8–G10 and G12 genotype reference sequences, green for genotype 7 sequences, red for genotype 4 sequences and blue for putative recombinant sequences.</p> Full article ">Figure 8
<p>Bayesian phylogenetic trees from clone sequences from isolate 4T. (<b>A</b>) Color representation of recombinant sequences with portions similar to genotype G4 in red and portions similar to genotype G7 in green. Horizontal brown lines indicate the location of inferred recombination breakpoints. Labeled rectangles in the upper part of figure (yellow, orange) refer to the coding sequences of antigenic determinants. Epitopes A, B, B′, D, D′, E, E′ (linear), F, G, H (conformational), ND1,2,3–neutralization domain, CD4+, CD8+, N5, N11 and N12–T cell epitopes, Zbp-Zinc-binding peptide, GYDP strong turn, THMR–transmembrane hydrophobic region, CXXC sequence in disulfide bond. (<b>B</b>,<b>C</b>) trees are based on two separate non-recombining regions of the <span class="html-italic">env</span> gene, identified through the Phylo-HMM algorithm and referred to as 5′ terminus 1–400 bp and 401–804 bp regions, respectively. Label names are shown in black for G1–G3, G5, G6, G8–G10 and G12 genotype reference sequences, green for genotype 7 sequences, red for genotype 4 sequences and blue for putative recombinant sequences.</p> Full article ">Figure 9
<p>Illustration of the putative recombination in BLV. The scheme illustrates the possible mechanisms of recombination as it might occur in BLV (<b>A</b>,<b>B</b>). BLV is a diploid retrovirus for which, when a host cell was simultaneously infected with two strains of BLV (belonged to G4:G4 and G7:G7) and hence harbored two different proviruses, the RNA transcript from each of the BLV proviruses could be incorporated into a single heterozygous virion (G4:G7). (<b>A</b>) When this virion subsequently infected a new B cell and template switching occurred during reverse transcription, a recombinant retroviral DNA sequence was generated, and all subsequent progeny virions were of this recombinant genotypes, for example, as was shown on the scheme for putative recombinant forms (G4/G7:G4/G7) and G4/G7/G4: G4/G7/G4. (<b>B</b>) The recombination would occur during heterozygous virion formation, already in the first passage (between the two co-infecting RNAs during heterozygous virion formation).</p> Full article ">
21 pages, 1419 KiB  
Review
Zika Virus—A Reemerging Neurotropic Arbovirus Associated with Adverse Pregnancy Outcomes and Neuropathogenesis
by Kenneth C. Elliott and Joseph J. Mattapallil
Pathogens 2024, 13(2), 177; https://doi.org/10.3390/pathogens13020177 - 15 Feb 2024
Viewed by 2250
Abstract
Zika virus (ZIKV) is a reemerging flavivirus that is primarily spread through bites from infected mosquitos. It was first discovered in 1947 in sentinel monkeys in Uganda and has since been the cause of several outbreaks, primarily in tropical and subtropical areas. Unlike [...] Read more.
Zika virus (ZIKV) is a reemerging flavivirus that is primarily spread through bites from infected mosquitos. It was first discovered in 1947 in sentinel monkeys in Uganda and has since been the cause of several outbreaks, primarily in tropical and subtropical areas. Unlike earlier outbreaks, the 2015–2016 epidemic in Brazil was characterized by the emergence of neurovirulent strains of ZIKV strains that could be sexually and perinatally transmitted, leading to the Congenital Zika Syndrome (CZS) in newborns, and Guillain-Barre Syndrome (GBS) along with encephalitis and meningitis in adults. The immune response elicited by ZIKV infection is highly effective and characterized by the induction of both ZIKV-specific neutralizing antibodies and robust effector CD8+ T cell responses. However, the structural similarities between ZIKV and Dengue virus (DENV) lead to the induction of cross-reactive immune responses that could potentially enhance subsequent DENV infection, which imposes a constraint on the development of a highly efficacious ZIKV vaccine. The isolation and characterization of antibodies capable of cross-neutralizing both ZIKV and DENV along with cross-reactive CD8+ T cell responses suggest that vaccine immunogens can be designed to overcome these constraints. Here we review the structural characteristics of ZIKV along with the evidence of neuropathogenesis associated with ZIKV infection and the complex nature of the immune response that is elicited by ZIKV infection. Full article
(This article belongs to the Special Issue Host Immune Responses to RNA Viruses, Volume II)
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<p>Cartoon structure of ZIKV and DENV particle and genome map. Zika virus and Dengue virus are members of the Flaviviridae family, containing a positive sense, single stranded ~10.5kb RNA genome. (<b>a</b>) ZIKV and DENV virions are enveloped and consist of three structural proteins, namely capsid (C), membrane (M), and envelope (E) proteins. Capsid proteins make up the icosahedral nucleocapsid that surrounds the genomic material. The M protein is only expressed on mature virions, it contains transmembrane regions, and is organized as a heterodimer underneath the E protein. The E protein contains the primary antigenic targets and is responsible for viral entry and assembly. (<b>b</b>) The genome encodes 3 structural genes (C, prM, E) and 7 nonstructural genes (NS1, NS2A, NS2B, NS3, NS4A, NS4B, NS5). NS2A assists with virion assembly through recruitment of the NS2BNS3 protease. NS2B dimerizes with NS3 to act as a protease and cleave the viral polypeptide.</p> Full article ">Figure 2
<p>Innate and adaptive immune response to ZIKV infection. (<b>a</b>) ZIKV infects target cells through receptor-mediated endocytosis and replicates in the cytoplasm. Replication intermediates such as single stranded and double stranded RNA are sensed by pathogen recognition receptors such as NLRP3, MDA5, TLR3, and RIG-I, which drives the activation and phosphorylation of IRF3 and IRF7, which translocate to the nucleus and drive the production of Type I IFNs. These Type I IFNs will be exported from the cell and interact with receptors on neighboring cells, leading to the phosphorylation and activation of the JAK/STAT pathway. Activation and phosphorylation of the JAK/STAT pathway leads to the recruitment of IRF9, which will translocate to the nucleus and bind to the Interferon Stimulated Response Element (ISRE), leading to the transcription of over 100 interferon stimulated genes (ISG) that induce an antiviral state. (<b>b</b>) Adaptive immune responses are characterized by the activation of ZIKV-specific CD8 cytotoxic T cells that recognize epitopes in the context of MHC Class I and eliminate infected cells through the release of the perforin and Granzyme B. ZIKV-specific CD8 T cell responses have been shown to recognize epitopes located within the prM, E, NS3, and NS5 proteins. ZIKV-specific adaptive B cell responses have been mapped to a number of proteins with neutralizing antibody responses primarily targeting the EDIII domain along with the E dimer epitope.</p> Full article ">Figure 3
<p>Sequence similarity between ZIKV and DENV E and NS1 proteins. (<b>a</b>) Phylogenetic tree and heat map showing the relatedness of ZIKV and DENV-1—4 E protein based on amino acid alignment. The NCBI Virus database [<a href="#B159-pathogens-13-00177" class="html-bibr">159</a>] (<a href="https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/" target="_blank">https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/</a> accessed on 30 October 2023) was used to download the reference sequences for E proteins of ZIKV and DENV-1—4. The sequences were then aligned using the online Clustal Omega Multiple Sequence Alignment (MSA) Tool [<a href="#B160-pathogens-13-00177" class="html-bibr">160</a>] (<a href="https://www.ebi.ac.uk/Tools/msa/clustalo/" target="_blank">https://www.ebi.ac.uk/Tools/msa/clustalo/</a> accessed on 30 October 2023). The resulting output was then pasted into the online “Simple Phylogeny” tool [<a href="#B160-pathogens-13-00177" class="html-bibr">160</a>] <a href="https://www.ebi.ac.uk/Tools/phylogeny/simple_phylogeny/" target="_blank">https://www.ebi.ac.uk/Tools/phylogeny/simple_phylogeny/</a> accessed on 30 October 2023). The phylogenic tree was then uploaded to iTOL [<a href="#B161-pathogens-13-00177" class="html-bibr">161</a>] (<a href="https://itol.embl.de/" target="_blank">https://itol.embl.de/</a> accessed on 30 October 2023) for visual enhancement and scaling. A heat map for amino acid identity was created from the Clustal Omega MSA. (<b>b</b>) Phylogenetic tree and heat map showing the relatedness of ZIKV and DENV-1–4 NS1 protein based on amino acid alignment. The NCBI Virus database [<a href="#B159-pathogens-13-00177" class="html-bibr">159</a>] (<a href="https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/" target="_blank">https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/</a> accessed on 30 October 2023) was used to download the reference sequences for the NS1 proteins of ZIKV and DENV-2–4; no reference sequence was available for DENV-1 NS1. As such, the exact similarity between ZIKV NS1 and DENV1 is not available. The sequences were then aligned using the online Clustal Omega Multiple Sequence Alignment Tool [<a href="#B160-pathogens-13-00177" class="html-bibr">160</a>] (<a href="https://www.ebi.ac.uk/Tools/msa/clustalo/" target="_blank">https://www.ebi.ac.uk/Tools/msa/clustalo/</a> accessed on 30 October 2023). The resulting output was then pasted into the online “Simple Phylogeny” tool [<a href="#B160-pathogens-13-00177" class="html-bibr">160</a>] (<a href="https://www.ebi.ac.uk/Tools/phylogeny/simple_phylogeny/" target="_blank">https://www.ebi.ac.uk/Tools/phylogeny/simple_phylogeny/</a> accessed on 30 October 2023). The phylogenetic tree was then uploaded to iTOL [<a href="#B161-pathogens-13-00177" class="html-bibr">161</a>] (<a href="https://itol.embl.de/" target="_blank">https://itol.embl.de/</a> accessed on 30 October 2023) for visual enhancement and scaling. The heat map for amino acid identity was created from the Clustal Omega MSA using Excel.</p> Full article ">
14 pages, 2151 KiB  
Article
Mapping the Silent Threat: A Comprehensive Analysis of Chagas Disease Occurrence in Riverside Communities in the Western Amazon
by Daniela da Silva Paixão, Fernanda Portela Madeira, Adila Costa de Jesus, Hêmilly Caroline da Silva Paixão, Juliana de Souza Almeida Aranha Camargo, Mariane Albuquerque Lima Ribeiro, Leandro José Ramos, Jader de Oliveira, João Aristeu da Rosa, Paulo Sérgio Bernarde, Antonieta Pereira Relvas, Sergio de Almeida Basano, Luis Marcelo Aranha Camargo and Dionatas Ulises de Oliveira Meneguetti
Pathogens 2024, 13(2), 176; https://doi.org/10.3390/pathogens13020176 - 15 Feb 2024
Viewed by 1332
Abstract
Chagas disease (CD) is a typical tropical illness caused by Trypanosoma cruzi. The objective of this study was to assess the prevalence of Chagas disease in communities in two states of the Brazilian Amazon. Data collection occurred in July in the Alto [...] Read more.
Chagas disease (CD) is a typical tropical illness caused by Trypanosoma cruzi. The objective of this study was to assess the prevalence of Chagas disease in communities in two states of the Brazilian Amazon. Data collection occurred in July in the Alto Juruá region of Acre and in December in the communities of Humaitá, Amazonas, in 2019. A total of 477 participants were included in the study. In the communities of Alto Juruá, triatomine collections and analyses of T. cruzi infection were also carried out. All confirmed cases were found in the state of Acre, resulting in a total prevalence of 1.67. Of these eight cases, seven underwent ECG, all of which were concluded as normal by the physician team’s cardiologists. Seventeen triatomine bugs, all belonging to the Rhodnius genus, were captured. The natural infection rate by T. cruzi was 25% in the Nova Cintra community and 66.67% in the Boca do Moa community (Alto Juruá). This research found that more than 1% of the studied population exhibited positive serological results for Chagas disease in the riverine communities during the study period, representing a small portion of cases among those who have not yet been diagnosed. Full article
(This article belongs to the Special Issue Insects Vectors of Pathogens)
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Figure 1
<p>Map of the study areas with the following descriptions: (<b>A</b>) Nova Cintra Community in the municipality of Cruzeiro do Sul, Acre, Brazil; (<b>B</b>) Boca do Moa Community in the municipality of Rodrigues Alves, Acre, Brazil; (<b>C</b>) Humaitá Communities, Amazonas, Brazil.</p> Full article ">Figure 2
<p>Collections in the Boca do Moa community, Cruzeiro do Sul, Acre, Brazil. (<b>A</b>) First day of collections at a local church; (<b>B</b>) realization of ECG; (<b>C</b>) second day of collections carried out at a daycare center; (<b>D</b>) preparation of slides and material for serology.</p> Full article ">Figure 3
<p>Collection in riverside communities of Humaitá, Amazonas, Brazil. (<b>A</b>) House in the Tabuleta community; (<b>B</b>) school in the Carará community; (<b>C</b>) church in the Creole community; (<b>D</b>) boats used to visit other communities.</p> Full article ">Figure 4
<p>Electrocardiogram of three patients with chronic Chagas disease. (<b>A</b>) Female patient, 50 years old; (<b>B</b>) female patient, 16 years old; (<b>C</b>) female patient, 30 years old.</p> Full article ">
9 pages, 1016 KiB  
Communication
First Molecular Data of Gongylonema pulchrum (Rhabditida: Gongylonematidae) in European Fallow Deer Dama dama from Romania
by Dan-Cornel Popovici, Ana-Maria Marin, Ovidiu Ionescu, Maria Monica Florina Moraru, Durmuș Alpaslan Kaya, Mirela Imre and Narcisa Mederle
Pathogens 2024, 13(2), 175; https://doi.org/10.3390/pathogens13020175 - 15 Feb 2024
Cited by 1 | Viewed by 1132
Abstract
Due to its adaptive versatility to numerous types of habitats, extremely diverse both in terms of composition and specificity, developed in various areas of the Western Plains of Romania, the European fallow deer (Dama dama) is a species with high ecological [...] Read more.
Due to its adaptive versatility to numerous types of habitats, extremely diverse both in terms of composition and specificity, developed in various areas of the Western Plains of Romania, the European fallow deer (Dama dama) is a species with high ecological plasticity. In this area, the D. dama interacts with other species of wild fauna but also with numerous domestic animals, an important aspect in terms of the sanitary-veterinary status of animal populations, as well as the existence of a potential risk of infection with various species of parasites that can cause the D. dama specimens to obtain certain diseases and even zoonoses. A total of 133 esophagi from D. dama have been examined for helminths. Of the 133 esophagus samples from D. dama, nematodes of the genus Gongylonema were identified in 25 (18.80%). Sequencing revealed that the nematode identified in the samples was 99% similar to the sequence of Gongylonema pulchrum (GenBank no. LC026018.1, LC388754.1, AB646061). The present research is the first report of the nematode G. pulchrum from D. dama in Romania. Full article
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<p>Map showing the geographical areas where <span class="html-italic">D. dama</span> were collected; green triangle shows the sites where female positive animals were found and purple squares shows the sites where male positive animals were found.</p> Full article ">Figure 2
<p>Esophagus of <span class="html-italic">D. dama</span> infected with <span class="html-italic">G. pulchrum</span>.</p> Full article ">
17 pages, 23562 KiB  
Article
Different Infectivity of Swine Enteric Coronaviruses in Cells of Various Species
by Zhongyuan Li, Yunyan Chen, Liang Li, Mei Xue and Li Feng
Pathogens 2024, 13(2), 174; https://doi.org/10.3390/pathogens13020174 - 15 Feb 2024
Cited by 2 | Viewed by 1735
Abstract
Swine enteric coronaviruses (SECoVs), including porcine deltacoronavirus (PDCoV), transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), and swine acute diarrhea syndrome coronavirus (SADS-CoV), have caused high mortality in piglets and, therefore, pose serious threats to the pork industry. Coronaviruses exhibit a trend [...] Read more.
Swine enteric coronaviruses (SECoVs), including porcine deltacoronavirus (PDCoV), transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), and swine acute diarrhea syndrome coronavirus (SADS-CoV), have caused high mortality in piglets and, therefore, pose serious threats to the pork industry. Coronaviruses exhibit a trend of interspecies transmission, and understanding the host range of SECoVs is crucial for improving our ability to predict and control future epidemics. Here, the replication of PDCoV, TGEV, and PEDV in cells from different host species was compared by measuring viral genomic RNA transcription and protein synthesis. We demonstrated that PDCoV had a higher efficiency in infecting human lung adenocarcinoma cells (A549), Madin–Darby bovine kidney cells (MDBK), Madin–Darby canine kidney cells (MDCK), and chicken embryonic fibroblast cells (DF-1) than PEDV and TGEV. Moreover, trypsin can enhance the infectivity of PDCoV to MDCK cells that are nonsusceptible to TGEV. Additionally, structural analyses of the receptor ectodomain indicate that PDCoV S1 engages Aminopeptidase N (APN) via domain II, which is highly conserved among animal species of different vertebrates. Our findings provide a basis for understanding the interspecies transmission potential of these three porcine coronaviruses. Full article
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<p>Infection of PDCoV, PEDV and TGEV in human A549 cells. (<b>A</b>) A549 cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 24 h, and the virus infection was analyzed by IFA. (<b>B</b>) The percentage of infected cells was determined by the formula (the number of infected cells/the number of total cells) × 100. (<b>C</b>) A549 cells were infected with TGEV, PEDV, and PDCoV (MOI = 0.02, 0.2 and 1) for 24 h, cells were lysed and detected by qPCR. Means and SD of the results from three independent experiments are shown. (<b>D</b>) A549 cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 2 h or 24 h, cells were lysed and detected by qPCR. *, <span class="html-italic">p</span> &lt; 0.05.**, <span class="html-italic">p</span> &lt; 0.01. ***, <span class="html-italic">p</span> &lt; 0.001. ****, <span class="html-italic">p</span> &lt; 0.0001. The <span class="html-italic">p</span> value was calculated using <span class="html-italic">t</span>-test.</p> Full article ">Figure 2
<p>Infection of PDCoV, PEDV and TGEV in MDBK cells. (<b>A</b>) MDBK cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 24 h, and the virus infection was analyzed by IFA. (<b>B</b>) The percentage of infected cells was determined by the formula (the number of infected cells/the number of total cells) × 100. (<b>C</b>) MDBK cells were infected with TGEV, PEDV, and PDCoV (MOI = 0.02, 0.2 and 1) for 24 h, cells were lysed and detected by qPCR. Means and SD of the results from three independent experiments are shown. **, <span class="html-italic">p</span> &lt; 0.01. ***, <span class="html-italic">p</span> &lt; 0.001. ****, <span class="html-italic">p</span> &lt; 0.0001. The <span class="html-italic">p</span> value was calculated using <span class="html-italic">t</span>-test.</p> Full article ">Figure 3
<p>Infection of PDCoV, PEDV and TGEV in MDCK cells. (<b>A</b>) MDCK cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 24 h, and the virus infection was analyzed by IFA. (<b>B</b>) The percentage of infected cells was determined by the formula (the number of infected cells/the number of total cells) × 100. (<b>C</b>) MDCK cells were infected with TGEV, PEDV, and PDCoV (MOI = 0.02, 0.2 and 1) for 24 h, cells were lysed and detected by qPCR. Means and SD of the results from three independent experiments are shown. (<b>D</b>) MDCK cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 2 h or 24 h, cells were lysed and detected by qPCR. (<b>E</b>) Vero-E6 cells were infected with the supernatant of PEDV-infected MDCK cells, and the virus infection was analyzed by IFA. *, <span class="html-italic">p</span> &lt; 0.05. **, <span class="html-italic">p</span> &lt; 0.01. ***, <span class="html-italic">p</span> &lt; 0.001. ****, <span class="html-italic">p</span> &lt; 0.0001. The <span class="html-italic">p</span> value was calculated using <span class="html-italic">t</span>-test.</p> Full article ">Figure 4
<p>Trypsin prompts the replication of PDCoV in MDCK cells. (<b>A</b>) PDCoV (MOI = 1) was incubated with MDCK cells for 24 h in the absence or presence of different doses of trypsin, washed three times with PBS and analyzed by IFA. (<b>B</b>) The percentage of infected cells was determined by the formula (the number of infected cells/the number of total cells) × 100. Means and SD of the results from three independent experiments are shown. ****, <span class="html-italic">p</span> &lt; 0.0001. The <span class="html-italic">p</span> value was calculated using <span class="html-italic">t</span>-test.</p> Full article ">Figure 5
<p>Infection of PDCoV, PEDV and TGEV in DF-1 cells. (<b>A</b>) DF-1 cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 24 h, and the virus infection was analyzed by IFA. (<b>B</b>) The percentage of infected cells was determined by the formula (the number of infected cells/the number of total cells) × 100. (<b>C</b>) DF-1 cells were infected with TGEV, PEDV, and PDCoV (MOI = 0.02, 0.2 and 1) for 24 h, cells were lysed and detected by qPCR. Means and SD of the results from three independent experiments are shown. **, <span class="html-italic">p</span> &lt; 0.01. ***, <span class="html-italic">p</span> &lt; 0.001. ****, <span class="html-italic">p</span> &lt; 0.0001. The <span class="html-italic">p</span> value was calculated using <span class="html-italic">t</span>-test.</p> Full article ">Figure 6
<p>Infection of PDCoV, PEDV and TGEV in Vero-E6 and BHK-21 cells. (<b>A</b>,<b>D</b>) Vero-E6 and BHK-21 cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 24 h, and the virus infection was analyzed by IFA. (<b>B</b>,<b>E</b>) The percentage of infected cells was determined by the formula (the number of infected cells/the number of total cells) × 100. (<b>C</b>,<b>F</b>) Vero-E6 and BHK-21 cells were infected with TGEV, PEDV, and PDCoV (MOI = 0.02, 0.2 and 1) for 24 h, cells were lysed and detected by qPCR. Means and SD of the results from three independent experiments are shown. *, <span class="html-italic">p</span> &lt; 0.05. **, <span class="html-italic">p</span> &lt; 0.01. ****, <span class="html-italic">p</span> &lt; 0.0001. The <span class="html-italic">p</span> value was calculated using <span class="html-italic">t</span>-test.</p> Full article ">Figure 7
<p>Infection of PDCoV, PEDV and TGEV in IPI-2I cells. (<b>A</b>) IPI-2I cells were infected with TGEV, PEDV, and PDCoV (MOI = 1) for 24 h, and the virus infection was analyzed by IFA. (<b>B</b>) The percentage of infected cells was determined by the formula (the number of infected cells/the number of total cells) × 100. (<b>C</b>) IPI-2I cells were infected with TGEV, PEDV, and PDCoV (MOI = 0.02, 0.2 and 1) for 24 h, cells were lysed and detected by qPCR. Means and SD of the results from three independent experiments are shown. ***, <span class="html-italic">p</span> &lt; 0.001. ****, <span class="html-italic">p</span> &lt; 0.0001. The <span class="html-italic">p</span> value was calculated using <span class="html-italic">t</span>-test.</p> Full article ">Figure 8
<p>Schematic representation of the APN protein with the different domains and virus–binding regions indicated. Virus–binding regions of TGEV, PEDV, and PDCoV are indicated, as previously reported [<a href="#B23-pathogens-13-00174" class="html-bibr">23</a>,<a href="#B26-pathogens-13-00174" class="html-bibr">26</a>,<a href="#B41-pathogens-13-00174" class="html-bibr">41</a>,<a href="#B42-pathogens-13-00174" class="html-bibr">42</a>]. The porcine APN amino acid sequence comparison with human, monkey, mouse, canine, bovine and chicken shows a homology range from 63.3% to 83.3%. When the virus-binding motif was compared, domain II is highly conserved across animal species of the different vertebrate classes.</p> Full article ">
10 pages, 276 KiB  
Article
Inflammatory Patterns Associated with Legionella in HIV and Pneumonia Coinfections
by Breanne M. Head, Adriana Trajtman, Ruochen Mao, Kathryn Bernard, Lázaro Vélez, Diana Marin, Lucelly López, Zulma Vanessa Rueda and Yoav Keynan
Pathogens 2024, 13(2), 173; https://doi.org/10.3390/pathogens13020173 - 14 Feb 2024
Viewed by 1449
Abstract
Legionella infections have a propensity for occurring in HIV-infected individuals, with immunosuppressed individuals tending to present with more severe disease. However, understanding regarding the Legionella host response in immune compromised individuals is lacking. This study investigated the inflammatory profiles associated with Legionella infection [...] Read more.
Legionella infections have a propensity for occurring in HIV-infected individuals, with immunosuppressed individuals tending to present with more severe disease. However, understanding regarding the Legionella host response in immune compromised individuals is lacking. This study investigated the inflammatory profiles associated with Legionella infection in patients hospitalized with HIV and pneumonia in Medellín, Colombia from February 2007 to April 2014, and correlated these profiles with clinical outcomes. Sample aliquots from the Colombian cohort were shipped to Canada where Legionella infections and systemic cytokine profiles were determined using real-time PCR and bead-based technology, respectively. To determine the effect of Legionella coinfection on clinical outcome, a patient database was consulted, comparing laboratory results and outcomes between Legionella-positive and -negative individuals. Principal component analysis revealed higher plasma concentrations of eotaxin, IP-10 and MCP-1 (p = 0.0046) during Legionella infection. Individuals with this immune profile also had higher rates of intensive care unit admissions (adjusted relative risk 1.047 [95% confidence interval 1.027–1.066]). Results demonstrate that systemic markers of monocyte/macrophage activation and differentiation (eotaxin, MCP-1, and IP-10) are associated with Legionella infection and worse patient outcomes. Further investigations are warranted to determine how this cytokine profile may play a role in Legionella pneumonia pathogenesis or immunity. Full article
(This article belongs to the Special Issue Immunity to Respiratory Infections)
13 pages, 614 KiB  
Article
A Comparative Study of Genetic Diversity and Multiplicity of Infection in Uncomplicated Plasmodium falciparum Infections in Selected Regions of Pre-Elimination and High Transmission Settings Using MSP1 and MSP2 Genes
by Olusegun Philip Akoniyon, Moses Akiibinu, Matthew A. Adeleke, Rajendra Maharaj and Moses Okpeku
Pathogens 2024, 13(2), 172; https://doi.org/10.3390/pathogens13020172 - 13 Feb 2024
Viewed by 1588
Abstract
Background: Understanding the genetic structure of P. falciparum population in different regions is pivotal to malaria elimination. Genetic diversity and the multiplicity of infection are indicators used for measuring malaria endemicity across different transmission settings. Therefore, this study characterized P. falciparum infections [...] Read more.
Background: Understanding the genetic structure of P. falciparum population in different regions is pivotal to malaria elimination. Genetic diversity and the multiplicity of infection are indicators used for measuring malaria endemicity across different transmission settings. Therefore, this study characterized P. falciparum infections from selected areas constituting pre-elimination and high transmission settings in South Africa and Nigeria, respectively. Methods: Parasite genomic DNA was extracted from 129 participants with uncomplicated P. falciparum infections. Isolates were collected from 78 participants in South Africa (southern Africa) and 51 in Nigeria (western Africa). Allelic typing of the msp1 and msp2 genes was carried out using nested PCR. Results: In msp1, the K1 allele (39.7%) was the most common allele among the South African isolates, while the RO33 allele (90.2%) was the most common allele among the Nigerian isolates. In the msp2 gene, FC27 and IC3D7 showed almost the same percentage distribution (44.9% and 43.6%) in the South African isolates, whereas FC27 had the highest percentage distribution (60.8%) in the Nigerian isolates. The msp2 gene showed highly distinctive genotypes, indicating high genetic diversity in the South African isolates, whereas msp1 showed high genetic diversity in the Nigerian isolates. The RO33 allelic family displayed an inverse relationship with participants’ age in the Nigerian isolates. The overall multiplicity of infection (MOI) was significantly higher in Nigeria (2.87) than in South Africa (2.44) (p < 0.000 *). In addition, heterozygosity was moderately higher in South Africa (1.46) than in Nigeria (1.13). Conclusions: The high genetic diversity and MOI in P. falciparum that were observed in this study could provide surveillance data, on the basis of which appropriate control strategies should be adopted. Full article
(This article belongs to the Special Issue Parasites Series: Parasitic Infection, Characterisation and Host Health, Parasitic Diversity and Host Range)
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<p>Genetic diversity in <span class="html-italic">msp1</span> (<b>a</b>) and <span class="html-italic">msp2</span> (<b>b</b>) in South African isolates; and in <span class="html-italic">msp1</span> (<b>c</b>) and <span class="html-italic">msp2</span> (<b>d</b>) in Nigerian isolates.</p> Full article ">
16 pages, 1354 KiB  
Article
Comparison of the Antibiotic Resistance of Escherichia coli Populations from Water and Biofilm in River Environments
by Aline Skof, Michael Koller, Rita Baumert, Jürgen Hautz, Fritz Treiber, Clemens Kittinger and Gernot Zarfel
Pathogens 2024, 13(2), 171; https://doi.org/10.3390/pathogens13020171 - 13 Feb 2024
Viewed by 3260
Abstract
Antibiotic-resistant, facultative pathogenic bacteria are commonly found in surface water; however, the factors influencing the spread and stabilization of antibiotic resistance in this habitat, particularly the role of biofilms, are not fully understood. The extent to which bacterial populations in biofilms or sediments [...] Read more.
Antibiotic-resistant, facultative pathogenic bacteria are commonly found in surface water; however, the factors influencing the spread and stabilization of antibiotic resistance in this habitat, particularly the role of biofilms, are not fully understood. The extent to which bacterial populations in biofilms or sediments exacerbate the problem for specific antibiotic classes or more broadly remains unanswered. In this study, we investigated the differences between the bacterial populations found in the surface water and sediment/biofilm of the Mur River and the Drava River in Austria. Samples of Escherichia coli were collected from both the water and sediment at two locations per river: upstream and downstream of urban areas that included a sewage treatment plant. The isolates were subjected to antimicrobial susceptibility testing against 21 antibiotics belonging to seven distinct classes. Additionally, isolates exhibiting either extended-spectrum beta-lactamase (ESBL) or carbapenemase phenotypes were further analyzed for specific antimicrobial resistance genes. E. coli isolates collected from all locations exhibited resistance to at least one of the tested antibiotics; on average, isolates from the Mur and Drava rivers showed 25.85% and 23.66% resistance, respectively. The most prevalent resistance observed was to ampicillin, amoxicillin–clavulanic acid, tetracycline, and nalidixic acid. Surprisingly, there was a similar proportion of resistant bacteria observed in both open water and sediment samples. The difference in resistance levels between the samples collected upstream and downstream of the cities was minimal. Out of all 831 isolates examined, 13 were identified as carrying ESBL genes, with 1 of these isolates also containing the gene for the KPC-2 carbapenemase. There were no significant differences between the biofilm (sediment) and open water samples in the occurrence of antibiotic resistance. For the E. coli populations in the examined rivers, the different factors in water and the sediment do not appear to influence the stability of resistance. No significant differences in antimicrobial resistance were observed between the bacterial populations collected from the biofilm (sediment) and open-water samples in either river. The different factors in water and the sediment do not appear to influence the stability of resistance. The minimal differences observed upstream and downstream of the cities could indicate that the river population already exhibits generalized resistance. Full article
(This article belongs to the Section Bacterial Pathogens)
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Graphical abstract

Graphical abstract
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<p>Proportions of resistance and multi-resistance in <span class="html-italic">E. coli</span> isolates from Mur and Drava water and sediment samples. The stacked columns represent the proportions of isolates showing the respective phenotype in all water and sediment samples. Blue columns indicate isolates susceptible to all antibiotics tested. Isolates with resistance to one or two classes of the tested antibiotics were classified as resistant (indicated in the orange part of the columns). Resistance to three or more classes of the tested antibiotics was classified as multi-resistance (indicated in the gray part of the columns).</p> Full article ">Figure 2
<p>Proportions of resistance and multi-resistance in <span class="html-italic">E. coli</span> isolates. Panel (<b>A</b>): Isolates from the Mur River. Panel (<b>B</b>): Isolates from the Drava River. Panel (<b>A</b>,<b>B</b>): The stacked columns represent the proportions of isolates showing the respective phenotype in the water and sediment samples from upstream and downstream of Graz (<b>A</b>) or Villach (<b>B</b>) and its WWTP. Blue columns indicate isolates susceptible to all antibiotics tested. Isolates with resistance to one or two classes of the tested antibiotics were classified as resistant (indicated in the orange part of the columns). Resistance to three or more classes of the tested antibiotics was classified as multi-resistant (indicated in the gray part of columns).</p> Full article ">Figure 3
<p>Proportions of <span class="html-italic">E. coli</span> isolates resistant to the tested antibiotics. Panel (<b>A</b>): Isolates from the Mur River. Panel (<b>B</b>): Isolates from the Drava River. Panel (<b>A</b>,<b>B</b>): Blue columns indicate isolates from the water samples, and orange columns indicate isolates from the sediment samples. * indicates a significant difference with a <span class="html-italic">p</span>-value less than 0.05. AM, ampicillin; AMC, amoxicillin–clavulanic acid; TZP, piperacillin/tazobactam; CN, cephalexin; CXM, cefuroxime; FOX, cefoxitin; CTX, cefotaxime; CAZ, ceftazidime; FEP, cefepime; AN: acrylonitrile; IPM, imipenem; CIP, ciprofloxacin; MXF, moxifloxacin; GM, gentamicin; SXT, trimethoprim/sulfamethoxazole; TE, tetracycline; NA, nalidixic acid; C, chloramphenicol.</p> Full article ">
13 pages, 1291 KiB  
Article
Neurodevelopmental Outcomes of Normocephalic Colombian Children with Antenatal Zika Virus Exposure at School Entry
by Sarah B. Mulkey, Elizabeth Corn, Meagan E. Williams, Colleen Peyton, Regan Andringa-Seed, Margarita Arroyave-Wessel, Gilbert Vezina, Dorothy I. Bulas, Robert H. Podolsky, Michael E. Msall and Carlos Cure
Pathogens 2024, 13(2), 170; https://doi.org/10.3390/pathogens13020170 - 13 Feb 2024
Cited by 2 | Viewed by 2231
Abstract
The long-term neurodevelopmental effects of antenatal Zika virus (ZIKV) exposure in children without congenital Zika syndrome (CZS) remain unclear, as few children have been examined to the age of school entry level. A total of 51 Colombian children with antenatal ZIKV exposure without [...] Read more.
The long-term neurodevelopmental effects of antenatal Zika virus (ZIKV) exposure in children without congenital Zika syndrome (CZS) remain unclear, as few children have been examined to the age of school entry level. A total of 51 Colombian children with antenatal ZIKV exposure without CZS and 70 unexposed controls were evaluated at 4–5 years of age using the Behavior Rating Inventory of Executive Function (BRIEF), the Pediatric Evaluation of Disability Inventory (PEDI-CAT), the Bracken School Readiness Assessment (BSRA), and the Movement Assessment Battery for Children (MABC). The mean ages at evaluation were 5.3 and 5.2 years for cases and controls, respectively. Elevated BRIEF scores in Shift and Emotional Control may suggest lower emotional regulation in cases. A greater number of cases were reported by parents to have behavior and mood problems. BSRA and PEDI-CAT activity scores were unexpectedly higher in cases, most likely related to the COVID-19 pandemic and a delayed school entry among the controls. Although PEDI-CAT mobility scores were lower in cases, there were no differences in motor scores on the MABC. Of 40 cases with neonatal neuroimaging, neurodevelopment in 17 with mild non-specific findings was no different from 23 cases with normal neuroimaging. Normocephalic children with ZIKV exposure have positive developmental trajectories at 4–5 years of age but differ from controls in measures of emotional regulation and adaptive mobility, necessitating continued follow-up. Full article
(This article belongs to the Special Issue Recent Advances in Pediatric Infectious Diseases)
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<p>A timeline of the 4–5-year evaluations of ZIKV-exposed cases and unexposed controls relative to the progression of the COVID-19 pandemic in the Department of Atlántico, Colombia. Created using publicly available COVID-19 case data from the Colombian Instituto Nacional de Salud (National Institute of Health) [<a href="#B10-pathogens-13-00170" class="html-bibr">10</a>].</p> Full article ">Figure 2
<p>Organization of study visits using the ZIKV Outcome Toolbox (originally described in Mulkey et al., 2023 [<a href="#B7-pathogens-13-00170" class="html-bibr">7</a>]). All study visits were completed in local community centers in Sabanalarga, Department of Atlántico, Colombia. Participants and adult family members completed multiple activity stations, each overseen by a trained study team member. Table and floor activities were recorded and monitored using telehealth Zoom by US team members.</p> Full article ">
14 pages, 11537 KiB  
Article
A Myeloid-Specific Lack of IL-4Rα Prevents the Development of Alternatively Activated Macrophages and Enhances Immunity to Experimental Cysticercosis
by Jonadab E. Olguín, Edmundo Corano-Arredondo, Victoria Hernández-Gómez, Irma Rivera-Montoya, Mario A. Rodríguez, Itzel Medina-Andrade, Berenice Arendse, Frank Brombacher and Luis I. Terrazas
Pathogens 2024, 13(2), 169; https://doi.org/10.3390/pathogens13020169 - 13 Feb 2024
Viewed by 1189
Abstract
To determine the role that the IL-4/IL13 receptor plays in the development of alternatively activated macrophages (AAM or M2) and their role in the regulation of immunity to the extraintestinal phase of the helminth parasite Taenia crassiceps, we followed the infection in [...] Read more.
To determine the role that the IL-4/IL13 receptor plays in the development of alternatively activated macrophages (AAM or M2) and their role in the regulation of immunity to the extraintestinal phase of the helminth parasite Taenia crassiceps, we followed the infection in a mouse strain lacking the IL-4Rα gene (IL-4Rα−/−) and in the macrophage/neutrophil-specific IL-4Rα-deficient mouse strain (LysMcreIL-4Rα−/lox or cre/LoxP). While 100% of T. crassiceps-infected IL-4Rα+/+ (WT) mice harbored large parasite loads, more than 50% of th eIL-4Rα−/− mice resolved the infection. Approximately 88% of the LysMcreIL-4Rα−/lox mice displayed a sterilizing immunity to the infection. The remaining few infected cre/LoxP mice displayed the lowest number of larvae in their peritoneal cavity. The inability of the WT mice to control the infection was associated with antigen-specific Th2-type responses with higher levels of IgG1, IL-4, IL-13, and total IgE, reduced NO production, and increased arginase activity. In contrast, IL-4Rα−/− semi-resistant mice showed a Th1/Th2 combined response. Furthermore, macrophages from the WT mice displayed higher transcripts for Arginase-1 and RELM-α, as well as increased expression of PD-L2 with robust suppressive activity over anti-CD3/CD28 stimulated T cells; all of these features are associated with the AAM or M2 macrophage phenotype. In contrast, both the IL-4Rα−/− and LysMcreIL-4Rα−/lox mice did not fully develop AAM or display suppressive activity over CD3/CD28 stimulated T cells, reducing PDL2 expression. Additionally, T-CD8+ but no T-CD4+ cells showed a suppressive phenotype with increased Tim-3 and PD1 expression in WT and IL-4Rα−/−, which were absent in T. crassiceps-infected LysMcreIL-4Rα−/lox mice. These findings demonstrate a critical role for the IL-4 signaling pathway in sustaining AAM and its suppressive activity during cysticercosis, suggesting a pivotal role for AAM in favoring susceptibility to T. crassiceps infection. Thus, the absence of these suppressor cells is one of the leading mechanisms to control experimental cysticercosis successfully. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Feature Papers in Infection and Immunity)
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<p>The absence of IL-4Rα signaling in macrophages favors resistance to <span class="html-italic">T. crassiceps</span> but does not change IL-4 production. The mice were infected with ten parasites and euthanized at marked times. (<b>A</b>) Parasite load in the peritoneal cavity at two, four, and eight weeks after infection in the WT, IL-4Rα<sup>−/−</sup>, and Cre/LoxP mouse strains. (<b>B</b>) Antigen-specific titers of IgG1 and IgG2a. (<b>C</b>) Detection of IL-4 and IL-13 in sera, and (<b>D</b>) IgE quantification in serum samples of infected mice from the three groups described at two, four, and eight weeks post-infection. Total data from 3 different experiments. Statistical differences were examined using one-way ANOVA with Tukey’s multiple comparisons post-test, considering significant a * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and **** <span class="html-italic">p</span> &lt; 0.0001.</p> Full article ">Figure 2
<p>Dual Th1 and Th2 cytokine production in the myeloid-specific absence of IL-4Rα signaling in macrophages during <span class="html-italic">T. crassiceps</span> infection. Splenocytes from the different groups described were stimulated with (<b>A</b>) anti-CD3/CD28 antibodies for 72 h or (<b>B</b>) <span class="html-italic">T. crassiceps</span> soluble extract for 96 hrs. Cytokines were evaluated using ELISA or CBA as described in the Materials and Methods. Total data are from 3 different experiments. Statistical differences were examined using one-way ANOVA with Tukey’s multiple comparisons post-test, considering significant a * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 3
<p>The myeloid-specific absence of IL-4Rα signaling induces a dual profile of macrophages. Cultured peritoneal exudate cells processed as described in the Materials and Methods were analyzed for <span class="html-italic">iNOS, ARG1, RELM-A, IL-4RA</span>, and <span class="html-italic">GAPDH</span> cDNA expression. (<b>A</b>) Representative and (<b>B</b>) total data. (<b>C</b>) Supernatants of cultured cells were analyzed for NO production and arginase activity. Total data from at least three different experiments. Statistical differences were examined using one-way ANOVA with Tukey’s multiple comparisons post-test, considering significant a * <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 4
<p>Reduced PDL2 percentage in the myeloid-specific absence of IL-4Rα signaling suggests an M1 profile during <span class="html-italic">T. crassiceps</span> infection. (<b>A</b>) Analysis strategy for (<b>B</b>) myeloid Ly6C and Ly6G cells in samples from the peritoneum in all of the experimental groups, with representative (upper) and total (lower) data from 3 different experiments. (<b>C</b>) Analysis strategy for (<b>D</b>) macrophages in samples from the peritoneum in all of the experimental groups, with representative (left) and total (right) data from 4 different experiments. (<b>E</b>) Co-culture of macrophages obtained from infected mice with naive CD90 cells as described in the Materials and Methods. Values are represented as counts per minute (CPM) from triplicate wells. Total data are from at least three different experiments. Statistical differences were examined using one-way ANOVA with Tukey’s multiple comparisons post-test, considering significant a * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 5
<p>The suppressive profile in CD8+ cells is reduced in the myeloid-specific absence of IL-4Rα signaling during <span class="html-italic">T. crassiceps</span> infection. (<b>A</b>) Analysis strategy for CD4<sup>+</sup> and CD8<sup>+</sup> T cells in samples from the peritoneum in all of the experimental groups, with representative (<b>B</b>) and total (<b>C</b>) data of CD4<sup>+</sup> and CD8<sup>+</sup> cells, following the analyses for (<b>D</b>) Tim-3, PD1, and CD25 percentages in the CD4<sup>+</sup> population or (<b>E</b>) Tim-3, PD1, and CD25 percentages in the CD8 population, with representative (left) or total (right) data from at least four different experiments. Statistical differences were examined using one-way ANOVA with Tukey’s multiple comparisons post-test, considering significant a ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">
17 pages, 2498 KiB  
Article
Comparing the Fate and Transport of MS2 Bacteriophage and Sodium Fluorescein in a Karstic Chalk Aquifer
by Daniel Matthews, Simon Bottrell, Landis Jared West, Louise Maurice, Andrew Farrant, Sarah Purnell and Danny Coffey
Pathogens 2024, 13(2), 168; https://doi.org/10.3390/pathogens13020168 - 13 Feb 2024
Viewed by 2038
Abstract
Groundwater flow and contaminant migration tracing is a vital method of identifying and characterising pollutant source-pathway-receptor linkages in karst aquifers. Bacteriophages are an attractive alternative tracer to non-reactive fluorescent dye tracers, as high titres (>1012 pfu mL−1) can be safely [...] Read more.
Groundwater flow and contaminant migration tracing is a vital method of identifying and characterising pollutant source-pathway-receptor linkages in karst aquifers. Bacteriophages are an attractive alternative tracer to non-reactive fluorescent dye tracers, as high titres (>1012 pfu mL−1) can be safely released into the aquifer, offering improved tracer detectability. However, the interpretation of bacteriophage tracer breakthrough curves is complicated as their fate and transport are impacted by aquifer physicochemical conditions. A comparative tracer migration experiment was conducted in a peri-urban catchment in southeast England to characterise the behaviour of MS2 bacteriophage relative to sodium fluorescein dye in a karstic chalk aquifer. Tracers were released into a stream sink and detected at two abstraction boreholes located 3 km and 10 km away. At both sites, the loss of MS2 phage greatly exceeded that of the solute tracer. In contrast, the qualitative shape of the dye and phage breakthrough curves were visually very similar, suggesting that the bacteriophage arriving at each site was governed by comparable transport parameters to the non-reactive dye tracer. The colloid filtration theory was applied to explain the apparent contradiction of comparable tracer breakthrough patterns despite massive phage losses in the subsurface. One-dimensional transport models were also fitted to each breakthrough curve to facilitate a quantitative comparison of the transport parameter values. The model results suggest that the bacteriophage migrates through the conduit system slightly faster than the fluorescent dye, but that the former is significantly less dispersed. These results suggest that whilst the bacteriophage tracer cannot be used to predict receptor concentrations from transport via karstic flow paths, it can provide estimates for groundwater flow and solute contaminant transit times. This study also provides insight into the attenuation and transport of pathogenic viruses in karstic chalk aquifers. Full article
(This article belongs to the Special Issue Viruses in Water)
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<p>Geological map of field area. The field area is located within the red rectangle on the locator map of the United Kingdom. Geological map data BGS ©.</p> Full article ">Figure 2
<p>Tracer breakthrough plots normalised to the injection concentration. Plot (<b>a</b>) is data from ABH1, and plot (<b>b</b>) is data from ABH2.Data from ABH1 are presented as log10(C/C<sub>0</sub>) to make a comparison clearer as the phage BTC is not visible when plotted as C/C<sub>0</sub>.</p> Full article ">Figure 3
<p>P<sub>i</sub>/FD<sub>i</sub> for the injection site and P<sub>r</sub>/FD<sub>r</sub> values for ABH1 (<span class="html-italic">L</span> = 2830 m) and ABH2 (<span class="html-italic">L</span> = 10,180 m).</p> Full article ">Figure 4
<p>C/M<sub>R</sub> tracer breakthrough plots. Plot (<b>a</b>) presents data from ABH1, and plot (<b>b</b>) presents data from ABH2.</p> Full article ">Figure 5
<p>Transport model fits for BTC data at ABH1 and ABH2. Plot (<b>a</b>) is sodium fluorescein data from ABH1, plot (<b>b</b>) is sodium fluorescein data from ABH2, plot (<b>c</b>) is MS2 phage data from ABH1, and plot (<b>d</b>) is MS2 phage data from ABH2.</p> Full article ">Figure 6
<p>Parameter estimates for MS2 phage tracer divided by corresponding estimates for fluorescein dye tracer.</p> Full article ">
10 pages, 4360 KiB  
Communication
Preservation of scRNA-Seq Libraries Using Existing Inactivation Protocols
by Gail L. Sturdevant, Kimberly D. Meade-White, Sonja M. Best and Emily Speranza
Pathogens 2024, 13(2), 167; https://doi.org/10.3390/pathogens13020167 - 13 Feb 2024
Cited by 1 | Viewed by 1694
Abstract
Single-cell RNA sequencing has soared in popularity in recent years. The ability to deeply profile the states of individual cells during the course of disease or infection has helped to expand our knowledge of coordinated responses. However, significant challenges arise when performing this [...] Read more.
Single-cell RNA sequencing has soared in popularity in recent years. The ability to deeply profile the states of individual cells during the course of disease or infection has helped to expand our knowledge of coordinated responses. However, significant challenges arise when performing this analysis in high containment settings such as biosafety level 3 (BSL-3), BSL-3+ and BSL-4. Working in containment is necessary for many important pathogens, such as Ebola virus, Marburg virus, Lassa virus, Nipah and Hendra viruses. Since standard operating procedures (SOPs) for inactivation are extensive and may compromise sample integrity, we tested whether the removal of single-cell sequencing libraries from containment laboratories using existing inactivation protocols for nucleic acid extraction (Trizol, RLT buffer, or AVL buffer) was feasible. We have demonstrated that the inactivation does not affect sample quality and can work with existing methods for inactivation. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Molecular Epidemiology, Diagnostics and Management of Viral Pathogens)
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<p>Overview of pre-processing of scRNA-Seq libraries. (<b>Top</b>) Marker expression of genes (columns) that identify the various cell types (rows). Average of normalized expression is shown in darker purple. (<b>Bottom</b>) UMAP projection with each point representing a different cell type colored by the cell annotation.</p> Full article ">Figure 2
<p>Overview of the 10X method for single-cell RNA seq library prep. The processes in step 1 (top blue box) are specific to the 10X Genomics protocol, but the processes in step 2 (bottom blue box) will be fairly conserved across all single-cell sequencing protocols. The steps in the blue boxes would all be carried out in the containment laboratory. The orange stars mark points in the protocol where there is a break and the sample can be stored for some time, allowing people to exit the lab. Sample stability and hands on time for each step is noted.</p> Full article ">Figure 3
<p>Comparison of 10X libraries with inactivation (blue) or without (normal, red). (<b>A</b>) Concentrations of libraries. (<b>B</b>) Average size of fragments. (<b>C</b>) Bioanalyzer trace comparison of a single sample before re-extraction (1:5 dilution) as compared with after (undiluted) using RLT buffer. <span class="html-italic">p</span>-values are determined by a Mann–Whitney test.</p> Full article ">Figure 4
<p>Comparison of inactivated samples to normal processed samples. (<b>A</b>) Stacked bar chart of the percent of the different myeloid cell subtypes detected per sample across the different conditions. (<b>B</b>) UMAP projections of the integrated data. The top is all the samples together with the inactivated samples in blue and the normal samples in red. The same projections with the type of post-library processing used can be observed below. (<b>C</b>) Violin plots of the number of unique mapped identifiers detected per cell in each sample. (<b>D</b>) Violin plot of the number of unique genes detected per cell across the 4 samples.</p> Full article ">
11 pages, 1086 KiB  
Article
Epidemiology of Ocular Thelaziosis in Domestic Dogs in Beijing
by Zichen Liu, Chang Yu, Xiaoli Tan, Ni Chen and Yipeng Jin
Pathogens 2024, 13(2), 166; https://doi.org/10.3390/pathogens13020166 - 12 Feb 2024
Viewed by 1193
Abstract
Thelazia callipaeda is a zoonotic parasitic nematode that lives in the ocular conjunctival sac of domestic and wild carnivores, lagomorphs, and humans, with Phortica spp. as its intermediate host. At present, the important role that domestic dogs play in thelaziosis has been studied [...] Read more.
Thelazia callipaeda is a zoonotic parasitic nematode that lives in the ocular conjunctival sac of domestic and wild carnivores, lagomorphs, and humans, with Phortica spp. as its intermediate host. At present, the important role that domestic dogs play in thelaziosis has been studied in many countries. However, Beijing, which is the first city in China to experience human thelaziosis, has not yet conducted a comprehensive epidemiological analysis of the disease. In this study, we analyzed risk factors (region, season, age, sex, breed, size, living environment, diet, country park travel history, immunization history, anthelmintic treatment history, and ocular clinical symptoms) associated with the prevalence of thelaziosis in domestic dogs in Beijing. The overall prevalence of T. callipaeda in the study area was 3.17% (102/3215 domestic dogs; 95% CI 2.57–3.78%). The results of the risk factor analysis showed that thelaziosis in domestic dogs from Beijing was significantly correlated with regional distribution, seasonal distribution, country park travel history, and anthelmintic treatment history (p < 0.05). In summer and autumn, domestic dogs living in mountainous areas, with a history of country park travel and without deworming were 4.164, 2.382, and 1.438 times more infected with T. callipaeda than those living in plain areas without a history of country park travel and with a history of deworming (OR = 4.164, OR = 2.382, OR = 1.438, respectively). T. callipaeda-infected domestic dogs did not always show any ocular clinical symptoms, while symptomatic domestic dogs were mainly characterized by moderate symptoms. The results indicate that in summer and autumn, preventive anthelmintic treatment should be strengthened for domestic dogs with a country park travel history or those living in mountain areas. At the same time, we should be vigilant about taking domestic dogs to play in country parks or mountainous areas during summer and autumn because this may pose a potential risk of the owner being infected with T. callipaeda. Full article
(This article belongs to the Special Issue Parasites: Epidemiology, Treatment and Control: 2nd Edition)
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<p>(<b>A</b>) <span class="html-italic">T. callipaeda</span> in the ocular conjunctival sac of a domestic dog. (<b>B</b>) Image of <span class="html-italic">T. callipaeda</span> showing the buccal capsule, pharynx, esophagus, cuticle striations, and vulva at the anterior end of a <span class="html-italic">T. callipaeda</span> female (arrow). (<b>C</b>) Larvae in a <span class="html-italic">T. callipaeda</span> female uterus (arrow). (<b>D</b>) The spicule at the posterior end of a <span class="html-italic">T. callipaeda</span> male (arrow).</p> Full article ">Figure 2
<p>Prevalence and geographical location of domestic dog thelaziosis in mountainous areas and plain areas of Beijing from 2018 to 2019. DC: Dongcheng District, XC: Xicheng District, CY: Chaoyang District, HD: Haidian District, FT: Fengtai District, SJS: Shijingshan District, CP: Changping District, DX: Daxing District, FS: Fangshan District, MTG: Mentougou District, MY: Miyun District, PG: Pinggu District, SY: Shunyi District, TZ: TongZhou District, YQ: Yanqing District, and HR: Huairou District. Maps were created using ArcGIS 10.8.</p> Full article ">
9 pages, 2668 KiB  
Case Report
Pseudopropionibacterium propionicum as a Cause of Empyema; A Diagnosis with Next-Generation Sequencing
by Sumbal Babar, Emily Liu, Savreet Kaur, Juzar Hussain, Patrick J. Danaher and Gregory M. Anstead
Pathogens 2024, 13(2), 165; https://doi.org/10.3390/pathogens13020165 - 12 Feb 2024
Viewed by 1419
Abstract
Pseudopropionibacterium propionicum (P.p.) is an anaerobic, Gram-positive, branching beaded rod that is a component of the human microbiome. An infection of the thoracic cavity with P.p. can mimic tuberculosis (TB), nocardiosis, and malignancy. We present a case of a 77-year-old male [...] Read more.
Pseudopropionibacterium propionicum (P.p.) is an anaerobic, Gram-positive, branching beaded rod that is a component of the human microbiome. An infection of the thoracic cavity with P.p. can mimic tuberculosis (TB), nocardiosis, and malignancy. We present a case of a 77-year-old male who presented with dyspnea and a productive cough who was initially misdiagnosed with TB based on positive acid-fast staining of a pleural biopsy specimen and an elevated adenosine deaminase level of the pleural fluid. He was then diagnosed with nocardiosis based on the Gram stain of his pleural fluid that showed a Gram-positive beaded and branching rod. The pleural fluid specimen was culture-negative, but the diagnosis of thoracic P.p. infection was determined with next-generation sequencing (NGS). The patient was initially treated with imipenem and minocycline, then ceftriaxone and minocycline, and later changed to minocycline only. This report shows the utility of NGS in making a microbiological diagnosis when other techniques either failed to provide a result (culture) or gave misleading information (histopathologic exam, pleural fluid adenosine deaminase determination, and organism morphology on Gram stain). Full article
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<p>CT scan of the chest on admission showing small right pleural effusion (blue arrow) and a loculated left pleural effusion with associated pleural and left hemidiaphragm thickening (red arrow). There was also an infiltrate in the lingula.</p> Full article ">Figure 2
<p>PET scan performed 4 days after the initial admission showing a large, tracer avid loculated pleural effusion in the left lung base measuring 14.5 cm × 2.8 cm × 11.0 cm, most consistent with chronic inflammation or infection. There was no primary lung mass or frank bony destruction, though there was some localized bone remodeling/periostitis.</p> Full article ">Figure 3
<p>Purulent fluid obtained from the initial thoracentesis.</p> Full article ">Figure 4
<p>Photomicrograph of the Gram stain of the pleural fluid showing beaded, branching Gram-positive rods initially thought to be <span class="html-italic">Nocardia</span> sp.</p> Full article ">Figure 5
<p>Repeat CT scan showed obstruction of the left mainstem bronchus and near complete collapse of the left lower lobe, bilateral pleural effusions, and peripheral atelectasis of the left upper lobe and lingula.</p> Full article ">Figure 6
<p>Taxonomic/nomenclature changes in <span class="html-italic">Pseudopropionibacterium propionicum</span> through the years.</p> Full article ">
25 pages, 2696 KiB  
Review
The Role of the Nuclear Factor-Kappa B (NF-κB) Pathway in SARS-CoV-2 Infection
by Periyanaina Kesika, Subramanian Thangaleela, Natarajan Sisubalan, Arumugam Radha, Bhagavathi Sundaram Sivamaruthi and Chaiyavat Chaiyasut
Pathogens 2024, 13(2), 164; https://doi.org/10.3390/pathogens13020164 - 12 Feb 2024
Cited by 1 | Viewed by 2231
Abstract
COVID-19 is a global health threat caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is associated with a significant increase in morbidity and mortality. The present review discusses nuclear factor-kappa B (NF-κB) activation and its potential therapeutical role in treating COVID-19. [...] Read more.
COVID-19 is a global health threat caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is associated with a significant increase in morbidity and mortality. The present review discusses nuclear factor-kappa B (NF-κB) activation and its potential therapeutical role in treating COVID-19. COVID-19 pathogenesis, the major NF-κB pathways, and the involvement of NF-κB in SARS-CoV-2 have been detailed. Specifically, NF-κB activation and its impact on managing COVID-19 has been discussed. As a central player in the immune and inflammatory responses, modulating NF-κB activation could offer a strategic avenue for managing SARS-CoV-2 infection. Understanding the NF-κB pathway’s role could aid in developing treatments against SARS-CoV-2. Further investigations into the intricacies of NF-κB activation are required to reveal effective therapeutic strategies for managing and combating the SARS-CoV-2 infection and COVID-19. Full article
(This article belongs to the Special Issue Reviews of Infectious Diseases)
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<p>NF-κB signaling (canonical and non-canonical) pathways. Several signals, including signals associated with immune receptors, could trigger the canonical pathways, which involve IKK complex activation by Tak1, IKK-mediated IκBα phosphorylation, and following degradation, consequential transient nuclear translocation of the prototypical NF-κB heterodimer P50/RelA. In the case of the non-canonical pathway, signals from a subset of TNFR members will trigger phosphorylation-induced p100 processing, and this pathway is NIK- and IKKα-dependent, not trimeric IKK complex-dependent, intervening in the persistent activation of the RelB/p52 complex. BAFFR: B-cell-activating factor belonging to TNF family receptor; BCR: B cell receptor; CD40: Cluster of differentiation 40; TLRs: Toll-like receptors; TNFR: Tumor necrosis factor (TNF) receptor; TCR: T cell receptor; LTβR: Lymphotoxin β-receptor; TAK1: IKK-activating kinase-1; IKK: IκB kinase; RANK: Receptor activator for nuclear factor κB; RelA: Protein of mammalian NF-κB family; NIK: NF-κB-inducing kinase (Recreated with permission based on Sun, 2011 [<a href="#B67-pathogens-13-00164" class="html-bibr">67</a>]).</p> Full article ">Figure 2
<p>Activation of the NF-kB signaling pathway induced by SARS-Co-V-2 and mediated by RIP/TRAF-dependent pathways or RIP-dependent/TRAF-independent IKKβ activation. The pathways activating NF-κB are RIP/TRAF-dependent pathways and RIP-dependent/TRAF-independent IKKβ activation, which may encompass antigen receptor signaling. Signaling to IKK downstream of RIPs and TRAFs involves several kinases implicated in NF-κB signaling pathways. Specifically, IKK activation is mediated by TAK1 in the TNF-alpha and IL-1 signaling pathways. RIP/TRAP-dependent pathways, including TNF receptor 1, IL-1 receptor, and TLR4 receptor signaling stimulated with their ligands (such as TNF-alpha, IL-1, and SARS-Co-V-2 spike proteins, respectively), recruit the binding of adaptor proteins such as RIP1-TRAF2-TRADD with TNF receptor 1, and MyD88-IRAK1-TRAF6 with the TLR4/IL-1 receptor. SARS-Co-V-2 spike proteins stimulate TLR4 signaling that recruits the binding of adopter protein TRIF, which leads to TAK1-mediated IKK activation. K63-linked polyubiquitin chain formation occurs by catalyzation with E3 ligase TRAF. K63-linked polyubiquitin chains bind to TAB2 and TAB3 subunits, thereby leading to the assembly and activation of the TAK1-TABs complex. IKKs bind to NEMO, forming an IKK-NEMO complex. The TAK1-TABs complex phosphorylates the IKKα and IKKβ present in the IKK-NEMO complex, leading to the activation of IKKs, which further activates transcription factor NF-κB (p65/p50). The transcription of NF-κB target genes leads to the expression of proinflammatory cytokines. LT-beta signaling-mediated alternative NF-κB activation through NIK is independent of TAK1, whereas NIK signaling mediates TAK1-dependent classical NF-κB activation. In RIP-dependent/TRAF-independent IKKβ activation, TNFα stimulates the TNF receptor 1, which induces the binding of adopter protein RIP that further recruits the IKK complex by direct interaction with NEMO and leads to IKKβ activation and NF-κB activation. NF-κB: Nuclear factor kappa B; RIP: Receptor-interacting protein; TRAF: tumor necrosis factor receptor (TNF-R)-associated factor; IKK: IκB kinase; MyD88: myeloid differentiation primary response protein 88; TRADD: TNFR-associated protein with a death domain; IRAK1: IL-1 receptor-associated kinase 1; IRAK4: IL-1 receptor-associated kinase 4; TAK1: Transforming growth factor-beta-activated kinase 1; TAB 1: TAK1-binding protein 1, TAB 2: TAK1-binding protein 2; TAB 3: TAK1-binding protein 3; NEMO: NF-κB essential modulator; TLR4: Toll-like receptor 4; TNF receptor: Tumor necrosis factor receptor; IL1: Interleukin 1; TNFα: Tumor necrosis factor-α; LTβ: Lymphotoxin β; NIK: NF-κB-inducing kinase.</p> Full article ">Figure 3
<p>SARS-CoV-2 papain-like protease inhibits the TLR3 and TLR7 signaling pathway-mediated inflammatory and antiviral response. Papain-like protease decreases the Lysine 63 (K63)-linked polyubiquitin chains of TRAF3 and TRAF6, which leads to reduced E3 ubiquitin ligase activity from TRAF3 and TRAF6, thereby preventing the activation of IRF-3 and NF-κB and further inhibiting TLR3- and TLR7-mediated expression of INF1 and proinflammatory cytokines. TLR3: Toll-like receptor 3; TLR7: Toll-like receptor 7; NF-κB: Nuclear factor kappa B; IRF-3: Interferon regulatory transcription factor 3; TRAF3: tumor necrosis factor receptor (TNF-R)-associated factor 3; TRAF6: tumor necrosis factor receptor (TNF-R)-associated factor 6; INF1: Interferon 1.</p> Full article ">Figure 4
<p>Cytokine storm induced by SARS-CoV-2 proteins (ORF7a, ORF3A, M, and N proteins) mediated by the activation of NF-kB. The structural viral proteins (M and N proteins) and predicted accessory viral proteins (ORF3a and ORF7a proteins) activate the NFκB signaling pathway. Among the 4 viral proteins, ORF7a is the most potent activator of proinflammatory cytokines, whose expression is mediated by NFκB activation. Cytokines such as IL-3, IL-4, and IL-7 were also upregulated by ORF7a. In addition, ORF7a promotes the expression of chemokines. The over-expression of cytokines further activates the NFκB pathway, resulting in the SARS-CoV-induced cytokine storm. * Significantly elevated in COVID-19 patients. ** Overexpression of cytokines further enhances NFκB activation. NFκB: Nuclear factor kappa B; ORF7a: Open-reading frame 7a; ORF3a: Open-reading frame 3a; M: Membrane protein; N: Nucleocapsid protein; IL: Interleukin; TNFα: Tumor necrosis factor-α; IFNβ: Interferon-β; CCL11, 17, 19, 20, 21, 25, 26, 27: Eosinophil chemotactic factors; CXCL9: Chemokine; ↑: Increased or upregulated.</p> Full article ">Figure 5
<p>Illustrates a diagrammatic representation of the intracellular signaling pathways activated by SARS-CoV-2 infection. Specific drugs targeting these pathways are repurposed to regulate the excessive release of cytokines induced by the viral infection. CCL3: Chemokine (C-C motif) ligand 3; G-CSF: Granulocyte-colony stimulating factor; GM-CSF: Granulocyte macrophage-colony stimulating factor; IκB: Inhibitor of nuclear factor-κB; JAK: Janus kinase; IL: Interleukin; IP-10: Interferon-γ-induced protein-10; MCP-1: Monocyte chemoattractant protein-1; MyD88: Myeloid differentiation primary response gene 88; NF-κB: Nuclear factor-κB; S1P: Sphingosine-1-phosphate; S1PR1: Sphingosine-1-phosphate receptor 1; STAT: Signal transducer and activator of transcription; TNFα: Tumor necrosis factor α; TLR: Tol-like receptor; TRIF: TIR-domain-containing adapter-inducing IFN-β. (Adapted and updated with permission from Catanzaro et al. [<a href="#B161-pathogens-13-00164" class="html-bibr">161</a>]).</p> Full article ">Figure 6
<p>A visual representation of how Jinhua Qinggan granules (JHQG) mitigate acute lung injury (ALI) induced by lipopolysaccharide (LPS) in mice. LPS triggers inflammatory responses through the TLR4/MyD88/NF-κB pathway, leading to excessive production of proinflammatory cytokines (such as TNF-α, IL-1β, and IL-6) and subsequent tissue damage. Furthermore, the activated NF-κB enhances the presence of anti-apoptotic proteins Mcl-1 and Bcl-xL, while inhibiting the activity of caspase 3/7, ultimately prolonging the survival of neutrophils. In contrast, treatment with JHQG suppresses the TLR4/MyD88/NF-κB pathway and facilitates neutrophil apoptosis by reducing Mcl-1 and Bcl-xL and activating caspase 3/7. This demonstrates the protective effect of JHQG in ALI. Bcl-xL: B-cell lymphoma-extra-large; NF-κB: Nuclear factor-κB; IL: Interleukin; TNFα: Tumor necrosis factor α; MyD88: Myeloid differentiation primary response gene 88; TLR: Tol-like receptor; Mcl-1: Myeloid leukemia 1 (Recreated based on Zhu et al. [<a href="#B162-pathogens-13-00164" class="html-bibr">162</a>]).</p> Full article ">
12 pages, 837 KiB  
Article
The Epidemiology of Anal Human Papillomavirus (HPV) in HIV-Positive and HIV-Negative Women and Men: A Ten-Year Retrospective Observational Study in Rome (Italy)
by Matteo Fracella, Giuseppe Oliveto, Piergiorgio Roberto, Lilia Cinti, Massimo Gentile, Eleonora Coratti, Gabriella D’Ettorre, Eugenio Nelson Cavallari, Francesco Romano, Letizia Santinelli, Luca Maddaloni, Federica Frasca, Carolina Scagnolari, Guido Antonelli and Alessandra Pierangeli
Pathogens 2024, 13(2), 163; https://doi.org/10.3390/pathogens13020163 - 11 Feb 2024
Cited by 2 | Viewed by 1842
Abstract
Human papillomaviruses (HPVs) commonly infect the anogenital mucosa; most infections are transient, but a fraction of those caused by high-risk (HR) types persist and may lead to anogenital cancer. The epidemiology of HPV genotypes in anal infections in groups at different risk for [...] Read more.
Human papillomaviruses (HPVs) commonly infect the anogenital mucosa; most infections are transient, but a fraction of those caused by high-risk (HR) types persist and may lead to anogenital cancer. The epidemiology of HPV genotypes in anal infections in groups at different risk for anal cancer has not been well described in Italy. This retrospective study reports the results of HPV DNA testing and complete genotyping performed on anal swabs from 691 female and male patients attending proctology clinics in Rome during 2012–2021; one-third had repeated testing. Cumulative HPV positivity in 1212 anal swabs was approximately 60%, was not age related, and showed an increasing trend over the study period. HPV rates differed significantly by sex and HIV status: HIV-negative women had the lowest (43.6%) and HIV-positive men the highest (83.5%) HPV prevalence. HIV-positive men had more oncogenic HPV genotypes detected, more multiple infections, and the highest frequency of persistent infections. Two-thirds of all infections were vaccine-preventable. This study found that anal HPV infection rates are still elevated and even increasing in groups at low and high risk of developing anal cancer. Prevention programs need to be improved to reduce rates of anal infection in young women and men. Full article
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<p>Distribution of identified genotypes in HPV-positive anal samples (N = 660) according to (<b>a</b>) IARC classification and (<b>b</b>) vaccine composition.</p> Full article ">Figure 2
<p>Distribution of HPV-positive results in anal specimens over ten consecutive years (2012–2021). The annual percentage of HPV-positive tests over the total number of tests is shown for the entire study group and for patients with known HIV status stratified in HIV-negative women, HIV-negative men, and HIV-positive men.</p> Full article ">
11 pages, 949 KiB  
Communication
Serological Evidence for Circulation of Influenza D Virus in the Ovine Population in Italy
by Gianvito Lanave, Michele Camero, Chiara Coppola, Serena Marchi, Giuseppe Cascone, Felice Salina, Miriana Coltraro, Amienwanlen E. Odigie, Emanuele Montomoli, Chiara Chiapponi, Vincenzo Cicirelli, Vito Martella and Claudia M. Trombetta
Pathogens 2024, 13(2), 162; https://doi.org/10.3390/pathogens13020162 - 11 Feb 2024
Viewed by 1632
Abstract
Influenza D virus (IDV) is a novel orthomyxovirus initially isolated from pigs exhibiting influenza-like disease in the USA. Since then, IDV has been detected worldwide in several host species, including livestock animals, whilst specific antibodies have been identified in humans, raising concerns about [...] Read more.
Influenza D virus (IDV) is a novel orthomyxovirus initially isolated from pigs exhibiting influenza-like disease in the USA. Since then, IDV has been detected worldwide in several host species, including livestock animals, whilst specific antibodies have been identified in humans, raising concerns about interspecies transmission and zoonotic risks. Few data regarding the seroprevalence of IDV in small ruminants have been available to date. In this study, we assessed the prevalence of antibodies against IDV in ovine serum samples in Sicily, Southern Italy. Six hundred serum samples, collected from dairy sheep herds located in Sicily in 2022, were tested by haemagglutination inhibition (HI) and virus neutralization (VN) assays using reference strains, D/660 and D/OK, representative of two distinct IDV lineages circulating in Italy. Out of 600 tested samples, 168 (28.0%) tested positive to either IDV strain D/660 or D/OK or to both by HI whilst 378 (63.0%) tested positive to either IDV strain D/660 or D/OK or to both by VN. Overall, our findings demonstrate that IDV circulates in ovine dairy herds in Sicily. Since IDV seems to have a broad host range and it has zoonotic potential, it is important to collect epidemiological information on susceptible species. Full article
(This article belongs to the Section Viral Pathogens)
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<p>Map of the study area within the European continent (<b>A</b>), the Italian country (<b>B</b>), the Sicily boundaries in Italy, (<b>C</b>) and the geographic distribution of dairy sheep herds in Ragusa and Syracuse prefectures (<b>D</b>).</p> Full article ">Figure 2
<p>Distribution of influenza D virus (IDV) positive antibody in ovine samples. The haemagglutination inhibition (HI) HI and virus neutralization (VN) VN titres ≥ 10 were used as the cut-off value for seropositive samples. Regarding the reference strain influenza D/bovine/Oklahoma/660/2013 (D/660), the highest positive rate HI titre was in the range 1/160 to 1/319 whilst the highest positive rate VN titre was ≥1280. Regarding the reference strain influenza D/swine/Italy/199724/2015 (D/OK), the highest positive rate HI titre was in the range 1/80 to 1/159 whilst the highest positive rate VN titre was in the range 1/640-1/1279.</p> Full article ">Figure 3
<p>Scatter plots of Abs titres obtained by haemagglutination inhibition (HI) and virus neutralization (VN) assays. Abs to influenza D/bovine/Oklahoma/660/2013 (D/660) (<b>A</b>) and influenza D/swine/Italy/199724/2015 (D/OK) (<b>B</b>) strains were assessed.</p> Full article ">
16 pages, 1600 KiB  
Article
Completing the Puzzle: A Cluster of Hunting Dogs with Tick-Borne Illness from a Fishing Community in Tobago, West Indies
by Roxanne A. Charles, Patricia Pow-Brown, Annika Gordon-Dillon, Lemar Blake, Soren Nicholls, Arianne Brown-Jordan, Joanne Caruth, Candice Sant, Indira Pargass, Asoke Basu, Emmanuel Albina, Christopher Oura and Karla Georges
Pathogens 2024, 13(2), 161; https://doi.org/10.3390/pathogens13020161 - 10 Feb 2024
Cited by 2 | Viewed by 1473
Abstract
Eight hunting dogs were visited by a state veterinarian on the island of Tobago, Trinidad and Tobago, West Indies, as owners reported anorexia and paralysis in five of their dogs. The veterinarian observed a combination of clinical signs consistent with tick-borne illness, including [...] Read more.
Eight hunting dogs were visited by a state veterinarian on the island of Tobago, Trinidad and Tobago, West Indies, as owners reported anorexia and paralysis in five of their dogs. The veterinarian observed a combination of clinical signs consistent with tick-borne illness, including fever, anorexia, anaemia, lethargy and paralysis. Blood and ticks were collected from each dog and submitted to a diagnostic laboratory for analysis. Microscopic analysis revealed a mixed infection of intracytoplasmic organisms consistent with Babesia spp. (erythrocyte) and Ehrlichia spp. (monocyte), respectively, from one dog, while a complete blood count indicated a regenerative anaemia (n = 1; 12.5%), non-regenerative anaemia (n = 4; 50%), neutrophilia (n = 3; 37.5%), lymphocytosis (n = 2; 25%), thrombocytopaenia (n = 3; 37.5%) and pancytopaenia (n = 1; 12.5%). DNA isolated from the eight blood samples and 20 ticks (16 Rhipicephalus sanguineus and 4 Amblyomma ovale) were subjected to conventional PCR and next-generation sequencing of the 16S rRNA and 18S rRNA gene for Anaplasma/Ehrlichia and Babesia/Theileria/Hepatozoon, respectively. The DNA of Ehrlichia spp., closely related to Ehrlichia canis, was detected in the blood of three dogs (37.5%), Anaplasma spp., closely related to Anaplasma marginale, in two (25%), Babesia vogeli in one dog (12.5%) and seven ticks (35%) and Hepatozoon canis and Anaplasma spp., in one tick (5%), respectively. These findings highlight the need to test both the vector and host for the presence of tick-borne pathogens when undertaking diagnostic investigations. Further studies are also warranted to elucidate the susceptibility of canids to Anaplasma marginale. Full article
(This article belongs to the Section Ticks)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Map of Tobago showing the location of the cluster of suspected canine TBD cases in Charlotteville. Map generated using the free and open source QGIS software.</p> Full article ">Figure 2
<p>Giemsa-stained peripheral blood smear of a dog (Dog 5) from Charlotteville, Tobago, showing an intra-erythrocytic inclusion body (<b>A</b>) consistent with <span class="html-italic">Babesia vogeli</span> and an intracytoplasmic mononuclear inclusion body (<b>B</b>) consistent with <span class="html-italic">Ehrlichia canis</span> (indicated by arrows).</p> Full article ">Figure 3
<p>Phylogenetic tree of selected representatives of <span class="html-italic">Anaplasma</span> and <span class="html-italic">Ehrlichia</span> spp. inferred from 16S rRNA. The evolutionary history was inferred by using the maximum likelihood method and the Kimura 2-parameter as the best-fit model. The tree with the highest log likelihood (−861.12) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying neighbour-joining and BioNJ algorithms to a matrix of pairwise distances estimated using the maximum composite likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The analysis contains <span class="html-italic">Ehrlichia</span> spp. The 16S rRNA sequences from dog blood (red diamonds; n = 3) and <span class="html-italic">Anaplasma</span> spp. sequences from dog blood (blue diamonds; n = 2) and an <span class="html-italic">A. ovale</span> tick (yellow diamond; n = 1), from Charlotteville, Tobago, together with nucleotide sequences from GenBank (no diamond; from canine blood), including Neorickettsia risticii as an outgroup. Sequence IDs are in the format accession number, pathogen and country of origin. Bootstrap values are represented as a per cent of internal branches (1000 replicates); values less than 70 are hidden. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 49 nucleotide sequences. All positions containing gaps and missing data were eliminated (complete deletion option). There were a total of 343 positions in the final dataset. Evolutionary analyses were conducted in MEGA11.</p> Full article ">Figure 4
<p>Phylogenetic tree of selected representatives of <span class="html-italic">Babesia vogeli</span> inferred from 18S rRNA. The evolutionary history was inferred by using the maximum likelihood method and Tamura–Nei as the best-fit model. The tree with the highest log likelihood (−3123.55) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying neighbour-joining and BioNJ algorithms to a matrix of pairwise distances estimated using the Tamura–Nei model, and then selecting the topology with a superior log likelihood value. The analysis contains <span class="html-italic">Babesia vogeli</span> 18S rRNA sequences derived from <span class="html-italic">R. sanguineus</span> ticks (red diamonds; n = 5) and <span class="html-italic">A. ovale</span> ticks (yellow diamond; n = 1) from dogs in Charlotteville, Tobago, together with 15 sequences from GenBank (no diamonds; all from canine blood), including the <span class="html-italic">Toxoplasma gondii</span> sequence (GenBank KX008033.1) as an outgroup. Sequence IDs are in the format accession number, pathogen and country of origin. Bootstrap values are represented as per cent of internal branches (1000 replicates); values less than 70 are hidden. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 21 nucleotide sequences. All positions containing gaps and missing data were eliminated (complete deletion option). There were a total of 1485 positions in the final dataset. Evolutionary analyses were conducted in MEGA11.</p> Full article ">
14 pages, 2255 KiB  
Article
In Vitro Sensitivity Test of Fusarium Species from Weeds and Non-Gramineous Plants to Triazole Fungicides
by Neringa Matelionienė, Renata Žvirdauskienė, Gražina Kadžienė, Evelina Zavtrikovienė and Skaidrė Supronienė
Pathogens 2024, 13(2), 160; https://doi.org/10.3390/pathogens13020160 - 10 Feb 2024
Cited by 1 | Viewed by 1644
Abstract
Fusarium species are common plant pathogens that cause serious crop losses worldwide. Fusarium spp. colonize not only the main host plants, crops, but also alternative hosts. The effectiveness of fungicide use in disease management ranges from very successful to possibly promoting the growth [...] Read more.
Fusarium species are common plant pathogens that cause serious crop losses worldwide. Fusarium spp. colonize not only the main host plants, crops, but also alternative hosts. The effectiveness of fungicide use in disease management ranges from very successful to possibly promoting the growth of the pathogen. Triazole fungicides are widely used to control these pathogens due to their broad-spectrum activity and systemic nature. This paper reviews the sensitivity of 40 Fusarium strains isolated from weeds, non-gramineous plants, and spring wheat to metconazole, prothioconazole, and tebuconazole. The effect of fungicides was determined by the percentage inhibition of F. graminearum, F. culmorum, F. sporotrichioides, and F. avenaceum fungal mycelial growth. The 50% effective concentration (EC50) values of all isolates on metconazole were lower than 2.9 mg L−1, prothioconazole EC50 ranged from 0.12 to 23.6 mg L−1, and tebuconazole ranged from 0.09 to 15.6 mg L−1. At 0.00025–0.025 mg L−1, the fungicides were ineffective, except for the growth of the F. avenaceum species. It was observed that isolates from weeds were more sensitive to low concentrations of fungicide than isolates from crop plants. In general, information is scarce regarding the comparison of fungicide resistance in Fusarium isolates from weed and crop plants, making this study an additional contribution to the existing knowledge base. Full article
(This article belongs to the Special Issue Current Research on Fusarium: 2nd Edition)
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<p>Mycelial growth inhibition (%) of four <span class="html-italic">Fusarium</span> species isolated from various plants at different concentrations of metconazole, prothioconazole, and tebuconazole. Fs—<span class="html-italic">F. sporotrichioides</span>, Fg—<span class="html-italic">F. graminearum</span>, Fc—<span class="html-italic">F. culmorum</span>, Fa—<span class="html-italic">F. avenaceum</span>. Concentrations: 1—0.00025, 2—0.0025, 3—0.025, 4—0.25, 5—2.5, 6—25 mg L<sup>−1</sup>. The black circle indicates the median inhibition values of all Fusarium isolates from the indicated host plant. The blue bar shows a range from the minimum to maximum values. Error bars indicate ± SE.</p> Full article ">Figure 2
<p>Mycelial growth inhibition (%) of all <span class="html-italic">Fusarium</span> isolates under the influence of different fungicides and their concentrations. The concentrations of fungicides indicated on the <span class="html-italic">Y</span>-axis are 1—0.00025, 2—0.0025, 3—0.025, 4—0.25, 5—2.5, 6—25 mg L<sup>−1</sup>. The black circle indicates the median inhibition values of all <span class="html-italic">Fusarium</span> isolates from the indicated host plant. The blue bar shows a range from the minimum to maximum values. Error bars indicate ±SE.</p> Full article ">Figure 3
<p>Mycelial growth inhibition of Fusarium sporotrichioides strain (45P) from wheat by different concentrations of metconazole (MET), prothioconazole (PRO), and tebuconazole (TEB). C—control plate without fungicides.</p> Full article ">
9 pages, 583 KiB  
Communication
Evaluation of Inactivation Methods for Rift Valley Fever Virus in Mouse Microglia
by Margarita V. Rangel, Feliza A. Bourguet, Carolyn I. Hall and Dina R. Weilhammer
Pathogens 2024, 13(2), 159; https://doi.org/10.3390/pathogens13020159 - 10 Feb 2024
Viewed by 4699
Abstract
Rift Valley fever phlebovirus (RVFV) is a highly pathogenic mosquito-borne virus with bioweapon potential due to its ability to be spread by aerosol transmission. Neurological symptoms are among the worst outcomes of infection, and understanding of pathogenesis mechanisms within the brain is limited. [...] Read more.
Rift Valley fever phlebovirus (RVFV) is a highly pathogenic mosquito-borne virus with bioweapon potential due to its ability to be spread by aerosol transmission. Neurological symptoms are among the worst outcomes of infection, and understanding of pathogenesis mechanisms within the brain is limited. RVFV is classified as an overlap select agent by the CDC and USDA; therefore, experiments involving fully virulent strains of virus are tightly regulated. Here, we present two methods for inactivation of live virus within samples derived from mouse microglia cells using commercially available kits for the preparation of cells for flow cytometry and RNA extraction. Using the flow cytometry protocol, we demonstrate key differences in the response of primary murine microglia to infection with fully virulent versus attenuated RVFV. Full article
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<p>Flow cytometric analysis of RVFV-infected primary microglial cells. Primary microglia were infected with RVFV MP-12 or ZH501, and at 16 h post infection cells were harvested for flow cytometry along with uninfected controls. The percentage of live cells are indicated as zombie yellow negative (<b>A</b>). Representative plots indicated CD45 and CD11b expression (<b>B</b>). The percentages of CD45<sup>hi</sup> CD11b<sup>hi</sup> cells were quantitated in the indicated conditions (<b>C</b>). The expression levels of CD86 (<b>D</b>) or CD80 (<b>E</b>) were assessed on uninfected, MP-12-infected or ZH501-infected cells, as indicated. Data in C-E are shown as the mean +/− SD of triplicate samples from a representative experiment performed twice. ns = not significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001.</p> Full article ">
18 pages, 12208 KiB  
Communication
Human Adenovirus Entry and Early Events during Infection of Primary Murine Neurons: Immunofluorescence Studies In Vitro
by Anna Słońska, Aleksandra Miedzińska, Marcin Chodkowski, Piotr Bąska, Aleksandra Mielnikow, Michalina Bartak, Marcin W. Bańbura and Joanna Cymerys
Pathogens 2024, 13(2), 158; https://doi.org/10.3390/pathogens13020158 - 9 Feb 2024
Viewed by 1412
Abstract
Human adenovirus (HAdV) is a common pathogen, which can lead to various clinical symptoms and—in some cases—central nervous system (CNS) dysfunctions, such as encephalitis and meningitis. Although the initial events of virus entry have already been identified in various cell types, the mechanism [...] Read more.
Human adenovirus (HAdV) is a common pathogen, which can lead to various clinical symptoms and—in some cases—central nervous system (CNS) dysfunctions, such as encephalitis and meningitis. Although the initial events of virus entry have already been identified in various cell types, the mechanism of neuronal uptake of adenoviruses is relatively little understood. The aim of this study was to investigate early events during adenoviral infection, in particular to determine the connection between cellular coxsackievirus and adenovirus receptor (CAR), clathrin, caveolin, and early endosomal proteins (EEA1 and Rab5) with the entry of HAdVs into primary murine neurons in vitro. An immunofluorescence assay and confocal microscopy analysis were carried out to determine HAdV4, 5, and 7 correlation with CAR, clathrin, caveolin, and early endosomal proteins in neurons. The quantification of Pearson’s coefficient between CAR and HAdVs indicated that the HAdV4 and HAdV5 types correlated with CAR and that the correlation was more substantial for HAdV5. Inhibition of clathrin-mediated endocytosis using chlorpromazine limited the infection with HAdV, whereas inhibition of caveolin-mediated endocytosis did not affect virus entry. Thus, the entry of tested HAdV types into neurons was most likely associated with clathrin but not caveolin. It was also demonstrated that HAdVs correlate with the Rab proteins (EEA1, Rab5) present in early vesicles, and the observed differences in the manner of correlation depended on the serotype of the virus. With our research, we strove to expand knowledge regarding the mechanism of HAdV entry into neurons, which may be beneficial for developing potential therapeutics in the future. Full article
(This article belongs to the Special Issue Host–Virus Interactions in the Nervous System)
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<p>Localization of CAR in mock-infected (<b>A</b>) and HAdVs-infected (10 min pi) (<b>B</b>) primary murine neurons. White arrows mark the virus and CAR accumulation sites, whereas white squares indicate regions where the fluorescence intensity measurement was detected. (<b>C</b>) Immunofluorescence analysis of HAdV4, 5, 7, and CAR localization. The line profile plots indicate the intensity distribution of green and red channels through the yellow lines in the magnified view of ROI in the merged panel. Red arrows show the overlay of the red and green channels. (<b>D</b>) Quantification of correlation employing Fiji/ImageJ Coloc 2 plugin: the graph represents Pearson’s coefficient of HAdV antigens and CAR correlation from ten independent fields of cells in two experiments (data represent mean ± standard error of the mean). CAR—red; HAdV antigens—green; DNA—blue. Scale bars: 20 µm.</p> Full article ">Figure 2
<p>Immunofluorescence images of clathrin and caveolin-1 in mock-infected (<b>A</b>) and HAdVs-infected (15 min pi) (<b>B</b>) primary murine neurons. A large amount of virions accumulated at the site of clathrin occurrence after internalization (white arrows). White squares indicate regions where the detection of fluorescence intensity measurement was performed. The line profile plots (<b>B</b>,<b>C</b>) indicate the intensity distribution of green and red channels through the yellow lines in the magnified view of ROI in the merged panel. Red arrows show an overlay of the red and green channels (<b>B</b>). Clathrin/caveolin proteins—red; HAdV antigens—green; DNA—blue. Scale bars: 10 µm (<b>A</b>,<b>B</b>), 20 µm (<b>C</b>).</p> Full article ">Figure 3
<p>Quantification of correlation between clathrin/caveolin and HAdV4, 5, 7 in murine neurons. Pearson’s correlation coefficients (r) were calculated from ten independent fields of cells in two different experiments employing Fiji/ImageJ Coloc 2 plugin. Data representing mean r ± standard error of the mean are indicated on bar charts.</p> Full article ">Figure 4
<p>Localization of the early endosomal proteins in primary murine neurons. Immunofluorescence images of EEA1 (<b>A</b>) and Rab5 (<b>B</b>) proteins in mock-infected neurons. EE markers (EEA1/Rab5)—red; DNA—blue. Scale bars: 10 µm.</p> Full article ">Figure 5
<p>Immunofluorescence images of EEA1 (<b>A</b>) and Rab5 (<b>C</b>) proteins in HAdV4-infected neurons at 15, 30, 60, and 120 min pi. White arrows mark the site of virus and EE markers’ accumulation, whereas white squares indicate regions where fluorescence intensity measurement was detected. The line profile plots (<b>B</b>,<b>D</b>) indicate the intensity distribution of green and red channels through the yellow lines in the magnified view of ROI in the merged panel. Red arrows show an overlay of the red (Rab5/EEA1) and green (HAdV4) channels. EE markers (EEA1/Rab5)—red; HAdV antigens—green; DNA—blue. Scale bars: 10 µm and 20 µm.</p> Full article ">Figure 6
<p>Immunofluorescence images of EEA1 (<b>A</b>) and Rab5 (<b>C</b>) proteins in HAdV5-infected neurons at 15, 30, 60, and 120 min pi. White arrows mark the site of virus and EE markers’ accumulation, whereas white squares indicate regions where fluorescence intensity measurement was detected. The line profile plots (<b>B</b>,<b>D</b>) indicate the intensity distribution of green and red channels through the yellow lines in the magnified view of ROI in the merged panel. Red arrows show an overlay of the red (Rab5/EEA1) and green (HAdV5) channels. EE markers (EEA1/Rab5)—red; HAdV antigens—green; DNA—blue. Scale bars: 10 µm and 20 µm.</p> Full article ">Figure 7
<p>Immunofluorescence images of EEA1 (<b>A</b>) and Rab5 (<b>C</b>) proteins in HAdV7-infected neurons at 15, 30, 60, and 120 min pi. White arrows mark the site of virus and EE markers’ accumulation, whereas white squares indicate regions where fluorescence intensity measurement was detected. The line profile plots (<b>B</b>,<b>D</b>) indicate the intensity distribution of green and red channels through the yellow lines in the magnified view of ROI in the merged panel. Red arrows show an overlay of the red (Rab5/EEA1) and green (HAdV7) channels. EE markers (EEA1/Rab5)—red; HAdV antigens—green; DNA—blue. Scale bars: 10 µm and 20 µm.</p> Full article ">Figure 8
<p>Quantification of correlation between EEA1/Rab5 proteins and HAdV4 (<b>A</b>), 5 (<b>B</b>), 7 (<b>C</b>) in murine neurons. Pearson’s correlation coefficients (r) were calculated from ten independent fields of cells in two different experiments employing the Fiji/ImageJ Coloc 2 plugin. Data representing mean r ± standard error of the mean are indicated on bar charts.</p> Full article ">Figure 9
<p>Inhibition of HAdV infection in primary murine neurons via chemical blocking of clathrin- and caveolin-mediated endocytosis. The effect of chlorpromazine and nystatin treatment on cell viability was measured by XTT assay (3 and 24 h treatment) (<b>A</b>,<b>B</b>). Cell viability was calculated as a percentage of viable, non-treated cells; columns represent the mean viability ± standard deviation (SD) (n = 3) after exposure to the inhibitor. Comparison of the viral DNA (copies/ng DNA) yield in mock-treated cells infected with HAdV 4, 5, or 7 and infected neurons treated with increasing concentrations of chlorpromazine (<b>C</b>,<b>E</b>,<b>G</b>) and nystatin (<b>D</b>,<b>F</b>,<b>H</b>) was performed by quantitative PCR (qPCR). Results are presented as mean ± SD of three experiments. Statistical comparisons were made between mock-treated HAdV-infected cells and HAdV-infected neurons treated with inhibitors (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p> Full article ">
16 pages, 1540 KiB  
Systematic Review
West Nile Virus Infection in Occupational Settings—A Systematic Review
by Amienwanlen E. Odigie, Angela Stufano, Valentina Schino, Aya Attia Koraney Zarea, Linda A. Ndiana, Daniela Mrenoshki, Iniobong C. I. Ugochukwu, Piero Lovreglio, Grazia Greco, Annamaria Pratelli, Michele Camero and Maria Tempesta
Pathogens 2024, 13(2), 157; https://doi.org/10.3390/pathogens13020157 - 9 Feb 2024
Cited by 2 | Viewed by 1804
Abstract
Background: West Nile virus (WNV) is an emerging mosquito-borne neurotropic virus, belonging to the Flaviviridae family and the Orthoflavivirus genus. The effective control of WNV requires a targeted preventive strategy that also needs the identification of the higher-risk populations. Hence, this study focused [...] Read more.
Background: West Nile virus (WNV) is an emerging mosquito-borne neurotropic virus, belonging to the Flaviviridae family and the Orthoflavivirus genus. The effective control of WNV requires a targeted preventive strategy that also needs the identification of the higher-risk populations. Hence, this study focused on a systematic literature review of WNV-acquired infection in work-related settings and the assessment of the exposure risks among different occupational categories. Methods: A comprehensive search was conducted to identify studies until September 2023 in multiple databases such as PubMed/MEDLINE, SCOPUS and Web of Science, according to the PRISMA 2020 statement. Risk of bias of collected papers was assessed by the ROB tool of the National Toxicology Program’s Office of Health Assessment and Translation handbook. Results: A total of 21 studies were included in the systematic review, out of which seventeen were observational studies and four were case reports. Workers identified as at higher risk for WNV infection were military workers, veterinarians, agricultural workers, farmers, and laboratory workers with contact with infected fluids or aerosols. Conclusions: The identification of higher-risk workers could facilitate active surveillance by occupational physicians, which could improve our understanding of the epidemiology of WNV and, in addition, could help tailor appropriate preventive recommendations, reducing the overall burden of disease in high-risk areas. Full article
(This article belongs to the Special Issue West Nile Virus and Other Zoonotic Infections)
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<p>PRISMA 2020 flow diagram.</p> Full article ">Figure 2
<p>Geographical location and WNV epidemic/endemic status at the time of data collection of the selected studies [<a href="#B21-pathogens-13-00157" class="html-bibr">21</a>,<a href="#B22-pathogens-13-00157" class="html-bibr">22</a>,<a href="#B23-pathogens-13-00157" class="html-bibr">23</a>,<a href="#B24-pathogens-13-00157" class="html-bibr">24</a>,<a href="#B25-pathogens-13-00157" class="html-bibr">25</a>,<a href="#B26-pathogens-13-00157" class="html-bibr">26</a>,<a href="#B27-pathogens-13-00157" class="html-bibr">27</a>,<a href="#B28-pathogens-13-00157" class="html-bibr">28</a>,<a href="#B29-pathogens-13-00157" class="html-bibr">29</a>,<a href="#B30-pathogens-13-00157" class="html-bibr">30</a>,<a href="#B31-pathogens-13-00157" class="html-bibr">31</a>,<a href="#B32-pathogens-13-00157" class="html-bibr">32</a>,<a href="#B33-pathogens-13-00157" class="html-bibr">33</a>,<a href="#B34-pathogens-13-00157" class="html-bibr">34</a>,<a href="#B35-pathogens-13-00157" class="html-bibr">35</a>,<a href="#B36-pathogens-13-00157" class="html-bibr">36</a>,<a href="#B37-pathogens-13-00157" class="html-bibr">37</a>].</p> Full article ">
14 pages, 959 KiB  
Article
Antibacterial Potential of Essential Oils and Silver Nanoparticles against Multidrug-Resistant Staphylococcus pseudintermedius Isolates
by Gabriele Meroni, Giulia Laterza, Alexios Tsikopoulos, Konstantinos Tsikopoulos, Sara Vitalini, Barbara Scaglia, Marcello Iriti, Luigi Bonizzi, Piera Anna Martino and Alessio Soggiu
Pathogens 2024, 13(2), 156; https://doi.org/10.3390/pathogens13020156 - 9 Feb 2024
Cited by 2 | Viewed by 1585
Abstract
Staphylococcus pseudintermedius is an emergent zoonotic agent associated with multidrug resistance (MDR). This work aimed to describe the antibacterial activity of four essential oils (EOs) and silver nanoparticles (AgNPs) against 15 S. pseudintermedius strains isolated from pyoderma. The four EOs, namely Rosmarinus officinalis [...] Read more.
Staphylococcus pseudintermedius is an emergent zoonotic agent associated with multidrug resistance (MDR). This work aimed to describe the antibacterial activity of four essential oils (EOs) and silver nanoparticles (AgNPs) against 15 S. pseudintermedius strains isolated from pyoderma. The four EOs, namely Rosmarinus officinalis (RO), Juniperus communis (GI), Citrus sinensis (AR), and Abies alba (AB), and AgNPs were used alone and in combination to determine the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC). All strains were MDR and methicillin-resistant. Among the antibiotic cohort, only rifampicin, doxycycline, and amikacin were effective. EOs’ chemical analysis revealed 124 compounds belonging to various chemical classes. Of them, 35 were found in AR, 75 in AB, 77 in GI, and 57 in RO. The monoterpenic fraction prevailed over the sesquiterpenic in all EOs. When EOs were tested alone, AB showed the lowest MIC followed by GI, AR, and RO (with values ranging from 1:128 to 1:2048). MBC increased in the following order: AB, AR, GI, and RO (with values ranging from 1:512 to 1:2048). MIC and MBC values for AgNPs were 10.74 mg/L ± 4.23 and 261.05 mg/L ± 172.74. In conclusion, EOs and AgNPs could limit the use of antibiotics or improve the efficacy of conventional therapies. Full article
(This article belongs to the Special Issue Exploring the Epidemiology, Pathogenicity, and Therapeutic Options of Staphylococcus spp.)
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<p>Pangenome-based UPGMA cluster analysis.</p> Full article ">Figure 2
<p>(<b>A</b>) UV-Vis absorption spectra of chemically-synthesized AgNPs; (<b>B</b>) TEM morphological analysis of NPs (scale bar corresponds to 200 nm).</p> Full article ">
19 pages, 1966 KiB  
Article
Aggregatibacter actinomycetemcomitans Cytolethal Distending Toxin Induces Cellugyrin-(Synaptogyrin 2) Dependent Cellular Senescence in Oral Keratinocytes
by Bruce J. Shenker, Jonathan Korostoff, Lisa P. Walker, Ali Zekavat, Anuradha Dhingra, Taewan J. Kim and Kathleen Boesze-Battaglia
Pathogens 2024, 13(2), 155; https://doi.org/10.3390/pathogens13020155 - 8 Feb 2024
Cited by 1 | Viewed by 1311
Abstract
Recently, we reported that oral-epithelial cells (OE) are unique in their response to Aggregatibacter actinomycetemcomitans cytolethal distending toxin (Cdt) in that cell cycle arrest (G2/M) occurs without leading to apoptosis. We now demonstrate that Cdt-induced cell cycle arrest in OE has a duration [...] Read more.
Recently, we reported that oral-epithelial cells (OE) are unique in their response to Aggregatibacter actinomycetemcomitans cytolethal distending toxin (Cdt) in that cell cycle arrest (G2/M) occurs without leading to apoptosis. We now demonstrate that Cdt-induced cell cycle arrest in OE has a duration of at least 7 days with no change in viability. Moreover, toxin-treated OE develops a new phenotype consistent with cellular senescence; this includes increased senescence-associated β-galactosidase (SA-β-gal) activity and accumulation of the lipopigment, lipofuscin. Moreover, the cells exhibit a secretory profile associated with cellular senescence known as the senescence-associated secretory phenotype (SASP), which includes IL-6, IL-8 and RANKL. Another unique feature of Cdt-induced OE senescence is disruption of barrier function, as shown by loss of transepithelial electrical resistance and confocal microscopic assessment of primary gingival keratinocyte structure. Finally, we demonstrate that Cdt-induced senescence is dependent upon the host cell protein cellugyrin, a homologue of the synaptic vesicle protein synaptogyrin. Collectively, these observations point to a novel pathogenic outcome in oral epithelium that we propose contributes to both A. actinomycetemcomitans infection and periodontal disease progression. Full article
(This article belongs to the Special Issue Aggregatibacter actinomycetemcomitans)
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<p>Cdt induces durable cell cycle arrest in OE. TIGK cells were treated with Cdt for varying periods of time as indicated and then monitored for cell cycle arrest. Panels (<b>A</b>) (control cells) and (<b>B</b>) (Cdt-treated cells) show the effect of Cdt (20 pg/mL) on TIGK proliferation after 72 h. Cell cycle progression was assessed using dual parameter flow cytometry; DNA content was assessed by monitoring propidium iodide fluorescence (PI-A) and incorporation of BrdU-FITC. Boxes indicate gates for cell cycle analysis: G1/G0 (black), G2/M (blue) and S (red); numbers indicate the percentage of cells within each gated box. Panel (<b>C</b>) shows the analysis of cell cycle progression in control (blue line) and toxin-treated (red line) cells stained with Viafluor 488 and incubated for 72 h. The results for panels (<b>A</b>–<b>C</b>) are each representative of three experiments. Panel (<b>D</b>) shows cell cycle analysis of TIGK cells treated with medium (blue) and Cdt [20 pg/mL; (red)] for 3–7 days using propidium iodide. Cells were analyzed for cell phase as described in <a href="#sec2-pathogens-13-00155" class="html-sec">Section 2</a>; the percentage of G2/M cells is plotted versus time. Results are compiled from three experiments and represent the mean ± SEM; all data points for Cdt-treated cells are significantly different from those observed in control cells (<span class="html-italic">p</span> &lt; 0.01). Individual cell cycle histograms are shown in <a href="#app1-pathogens-13-00155" class="html-app">Figure S1</a>.</p> Full article ">Figure 2
<p>Cdt induces a cellular senescent phenotype in OEs characterized by increases in both SA-β-gal activity and lipofuscin content. TIGK cells were treated with 0–25 pg/mL Cdt for 72 h and then analyzed for SA-β-gal activity as described in <a href="#sec2-pathogens-13-00155" class="html-sec">Section 2</a>. Data are plotted as fluorescence (MCF) vs. Cdt concentration. The inset (panel (<b>A</b>)) shows results for exposure to Cdt for 7 days. Panel (<b>B</b>) shows the effect of Cdt on SA-β-gal activity in toxin-treated PGK cells following 3 days of exposure to Cdt. Panel (<b>C</b>) shows the effect of Cdt (20 pg/mL) on lipofuscin levels in TIGK cells following 3–7 days of exposure to toxin. Lipofuscin was detected using biotinylated SenTraGor, followed by staining with an anti-biotin antibody conjugated to AF488. Results are plotted as fluorescence (MCF) versus time of exposure to Cdt (days). Panel (<b>D</b>) shows the effect of Cdt on lipofuscin levels in PGK cells after 4 days of treatment with toxin. Results are plotted as the MCF (mean ± SEM) of three experiments; * indicates statistical significance (<span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 3
<p>Cdt induces SASP in TIGK cells. TIGK cells were treated with Cdt (0–100 pg/mL) for 72 h; cell supernatants were harvested and analyzed by ELISA for release of IL-8 (panel (<b>A</b>)), IL-6 (panel (<b>B</b>)) and RANKL (panel (<b>C</b>)). In a second series of experiments, TIGK cells were pre-treated with the GSDMD inhibitor NSA (0–1 μM) for one h, followed by the addition of Cdt (100 pg/mL). Supernatants were harvested 72 h later and analyzed for release of IL-8 (panel (<b>D</b>)), IL-6 (panel (<b>E</b>)) and RANKL (panel (<b>F</b>)). Results are the mean ± SEM of three experiments; * indicates statistical significance (<span class="html-italic">p</span> &lt; 0.01).</p> Full article ">Figure 4
<p>Cdt-induced OE senescent cells exhibit a breakdown in epithelial barrier function. PGKs were grown to confluence until a stable TEER was established. Medium or Cdt was then added and the cells assessed daily for changes in TEER as described in <a href="#sec2-pathogens-13-00155" class="html-sec">Section 2</a>. Results of three experiments were plotted as mean resistance (Ω × cm<sup>2</sup>) at 24 h (solid bars), 48 h (hatched bars) and 72 h (cross hatched bars); * indicates statistical significance (<span class="html-italic">p</span> &lt; 0.01).</p> Full article ">Figure 5
<p>Cdt treatment alters cell–cell contacts in PGKs. (<b>A</b>) Confocal images showing control (untreated) and Cdt (10 pg/mL, 48 h)-treated PGKs immunostained with ß-catenin (green). Nuclei stained with Hoechst are pseudo-colored in cyan. (<b>B</b>) Boxed regions in the panel (<b>A</b>) were enlarged and shown. (<b>C</b>) The boxed regions in panel (<b>B</b>) were further enlarged, highlighting the appearance of distinct gaps between cells in the Cdt-treated set (right) relative to the control cells. (<b>D</b>) Line intensity profiles for ß-catenin (green) and Hoechst nuclear stain (cyan) across the white dotted line in panel (<b>C</b>). The gaps between the adjacent cells identified by the ß-catenin staining pattern are depicted by dotted black lines.</p> Full article ">Figure 6
<p>Cdt-induced cellular senescence is dependent on the host cell protein cellugyrin. Cellugyrin-deficient TIGK cells (TIGK<sup>Cg−</sup>) were prepared using CRISPR/Cas9 gene editing (inset panel (<b>A</b>)). In panel A, TIGK<sup>Cg−</sup> (cross-hatched bars) were compared with TIGK<sup>WT</sup> cells (solid bars) for susceptibility to Cdt-induced cell cycle arrest. The percentage of G2/M cells was determined using propidium iodide fluorescence and flow cytometry; the results are plotted as the percentage of G2/M cells (mean ± SEM) versus Cdt concentration. Panel (<b>B</b>) compares the effect of Cdt (10 pg/mL) on TIGK<sup>WT</sup> and TIGK<sup>Cg−</sup> cell SA-β-gal activity after 72 h; the data are plotted as SA-β-gal fluorescence [MCF; (mean ± SEM)]. Panel (<b>C</b>) shows the effect of Cdt on lipofuscin content in TIGK<sup>WT</sup> and TIGK<sup>Cg−</sup> cells following 96 h exposure to the toxin; results are plotted as lipofuscin content [MCF; (mean ± SEM)]. * indicates statistical significance (<span class="html-italic">p</span> &lt; 0.05) when compared to similarly treated TIGK<sup>WT</sup> cells.</p> Full article ">Figure 7
<p>Model depicting the role of <span class="html-italic">Aa</span>Cdt-induced senescence in the pathogenesis of MIPP. The left panel shows healthy tissue at risk for MIPP due to the presence of supragingival <span class="html-italic">A. actinomycetemcomitans</span> (<span class="html-italic">Aa</span>). Initial exposure to <span class="html-italic">Aa</span>Cdt occurs while the bacteria are at the gingival margin, leading to cell cycle arrest and senescence within the epithelium and concomitant loss of barrier function indicated as distinct gaps between epithelial cells (middle panel). Continued exposure to Cdt along with OE-derived SASP-associated proinflammatory mediators further contribute to increased OE senescence and translocation of <span class="html-italic">A. actinomycetemcomitans</span> into the subgingival tissue (right panel); collectively, the mediators contribute to an altered gingival microenvironment conducive to supporting infection by inflammophilic organisms. Noteworthy, continued exposure to <span class="html-italic">Aa</span>Cdt and/or SASP perpetuates the induction of OE senescence (and possibly fibroblasts) in the face of constant epithelial turnover. Ultimately, these events lead to the recruitment of both innate and acquired immune cells, chronic inflammation and bone destruction.</p> Full article ">
19 pages, 2526 KiB  
Article
A Deep Sequencing Strategy for Investigation of Virus Variants within African Swine Fever Virus-Infected Pigs
by Camille Melissa Johnston, Ann Sofie Olesen, Louise Lohse, Agnete le Maire Madsen, Anette Bøtner, Graham J. Belsham and Thomas Bruun Rasmussen
Pathogens 2024, 13(2), 154; https://doi.org/10.3390/pathogens13020154 - 8 Feb 2024
Viewed by 1827
Abstract
African swine fever virus (ASFV) is the causative agent of African swine fever, an economically important disease of pigs, often with a high case fatality rate. ASFV has demonstrated low genetic diversity among isolates collected within Eurasia. To explore the influence of viral [...] Read more.
African swine fever virus (ASFV) is the causative agent of African swine fever, an economically important disease of pigs, often with a high case fatality rate. ASFV has demonstrated low genetic diversity among isolates collected within Eurasia. To explore the influence of viral variants on clinical outcomes and infection dynamics in pigs experimentally infected with ASFV, we have designed a deep sequencing strategy. The variant analysis revealed unique SNPs at <10% frequency in several infected pigs as well as some SNPs that were found in more than one pig. In addition, a deletion of 10,487 bp (resulting in the complete loss of 21 genes) was present at a nearly 100% frequency in the ASFV DNA from one pig at position 6362-16849. This deletion was also found to be present at low levels in the virus inoculum and in two other infected pigs. The current methodology can be used for the currently circulating Eurasian ASFVs and also adapted to other ASFV strains and genotypes. Comprehensive deep sequencing is critical for following ASFV molecular evolution, especially for the identification of modifications that affect virus virulence. Full article
(This article belongs to the Section Viral Pathogens)
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<p>Detection of ASFV DNA by qPCR [<a href="#B35-pathogens-13-00154" class="html-bibr">35</a>] in EDTA blood of the different pigs collected on day of euthanasia (PID 6).</p> Full article ">Figure 2
<p>PCR schematic of the overlapping long PCRs.</p> Full article ">Figure 3
<p>Deletion screening on samples collected on day of euthanasia. (<b>A</b>) PCR with primers covering nt 6188-17145. L1: Genomic Ladder, L2: GeneRuler 1kb plus, Inoc: Inoculum, E1: Pig 1 EDTA-blood, E2: Pig 2 EDTA-blood, E4: Pig 4 EDTA-blood, E7: Pig 7 EDTA-blood, E8: Pig 8 EDTA-blood, E9: Pig 9 EDTA-blood, E10: Pig 10 EDTA-blood, E11: Pig 11 EDTA-blood, E12: Pig 12 EDTA-blood. (<b>B</b>) PCR with primers covering nt 6188-17145. L1: Genomic Ladder, L2: GeneRuler 1kb plus, E8: Pig 8 EDTA-blood, B8: Pig 8 bone-marrow, SP8: Pig 8 spleen, S8: Pig 8 serum. (<b>C</b>) PCR with primers covering nt 6708-7668. L1: D5000 Ladder, L2: GeneRuler 1kb plus, Inoc: Inoculum, E1: Pig 1 EDTA-blood, E2: Pig 2 EDTA-blood, E4: Pig 4 EDTA-blood, E7: Pig 7 EDTA-blood, E8: Pig 8 EDTA-blood, E9: Pig 9 EDTA-blood, E10: Pig 10 EDTA-blood, E11: Pig 11 EDTA-blood, E12: Pig 12 EDTA-blood. (<b>D</b>) PCR with primers covering nt 6708-7668. L1: D5000 Ladder, L2: GeneRuler 1kb plus, E8: Pig 8 EDTA-blood, B8: Pig 8 bone-marrow, SP8: Pig 8 spleen, S8: Pig 8 serum. Green and purple bands indicate lower and upper molecular weight markers, respectively, whereas arrows indicate bands detected by the TapeStation Analysis software.</p> Full article ">Figure 4
<p>Variant frequency (Lo-Freq) plots of silent (green), missense (red), other (blue), insertion (purple), and deletion (orange) mutations. Grey background indicates areas with no PCR coverage. Genes on the forward strand are indicated in blue, and genes on the reverse strand are indicated in gold, with affected genes in dark grey. (<b>A</b>) SNP frequencies in Inoculum. (<b>B</b>) SNP frequencies in EDTA blood pig 1. (<b>C</b>) SNP frequencies in EDTA blood pig 2. (<b>D</b>) SNP frequencies in EDTA blood pig 4. (<b>E</b>) SNP frequencies in EDTA blood pig 7. (<b>F</b>) SNP frequencies in EDTA blood pig 8. (<b>G</b>) SNP frequencies in EDTA blood pig 9. (<b>H</b>) SNP frequencies in EDTA blood pig 10. (<b>I</b>) SNP frequencies in EDTA blood pig 11. (<b>J</b>) SNP frequencies in EDTA blood pig 12.</p> Full article ">Figure 4 Cont.
<p>Variant frequency (Lo-Freq) plots of silent (green), missense (red), other (blue), insertion (purple), and deletion (orange) mutations. Grey background indicates areas with no PCR coverage. Genes on the forward strand are indicated in blue, and genes on the reverse strand are indicated in gold, with affected genes in dark grey. (<b>A</b>) SNP frequencies in Inoculum. (<b>B</b>) SNP frequencies in EDTA blood pig 1. (<b>C</b>) SNP frequencies in EDTA blood pig 2. (<b>D</b>) SNP frequencies in EDTA blood pig 4. (<b>E</b>) SNP frequencies in EDTA blood pig 7. (<b>F</b>) SNP frequencies in EDTA blood pig 8. (<b>G</b>) SNP frequencies in EDTA blood pig 9. (<b>H</b>) SNP frequencies in EDTA blood pig 10. (<b>I</b>) SNP frequencies in EDTA blood pig 11. (<b>J</b>) SNP frequencies in EDTA blood pig 12.</p> Full article ">Figure 5
<p>Variant frequency (Lo-Freq) plots of silent (green), missense (red), other (blue), insertion (purple), and deletion (orange) mutations. Grey background indicates areas with no PCR coverage. Genes on the forward strand are indicated in blue, and genes on the reverse strand are indicated in gold, with affected genes in dark grey. (<b>A</b>) SNP frequencies in Inoculum. (<b>B</b>) SNP frequencies in EDTA blood pig 2. (<b>C</b>) SNP frequencies in bone marrow pig 2. (<b>D</b>) SNP frequencies in spleen pig 2. (<b>E</b>) SNP frequencies in serum pig 2.</p> Full article ">
9 pages, 784 KiB  
Communication
Prevalence of Toxoplasma gondii in Wild American Mink (Neogale vison): The First Serological Study in Germany and Poland
by Mike Heddergott, Jutta Pikalo, Franz Müller, Natalia Osten-Sacken and Peter Steinbach
Pathogens 2024, 13(2), 153; https://doi.org/10.3390/pathogens13020153 - 7 Feb 2024
Cited by 1 | Viewed by 1647
Abstract
Toxoplasma gondii is an obligate intracellular protozoan that causes toxoplasmosis in warm-blooded animals. Although most infections in humans and animals are subclinical, an infection can nevertheless be fatal. One of the important characteristics in the epidemiology of this parasite is waterborne transmission. The [...] Read more.
Toxoplasma gondii is an obligate intracellular protozoan that causes toxoplasmosis in warm-blooded animals. Although most infections in humans and animals are subclinical, an infection can nevertheless be fatal. One of the important characteristics in the epidemiology of this parasite is waterborne transmission. The American mink (Neogale vison), a mammal closely adapted to freshwater ecosystems, is a potential sentinel for T. gondii. We analysed meat juice from the heart of 194 wild minks collected between 2019 and 2022 in five study areas from Germany and Poland and tested for the presence of antibodies against T. gondii. The analysis was performed using a commercial enzyme-linked immunosorbent assay test (ELISA). Antibodies were detected in 45.36% (88/194, 95% confidence interval (CI): 38.39–52.41%) of the analysed animals. While the prevalence values ranged from 37.50% to 49.30%, there was no significant difference in seroprevalence between the study areas. Juveniles were less likely to carry T. gondii antibodies than adults (odds ratio: 0.216), whereas there was no significant difference in prevalence between the sexes (odds ratio: 0.933). The results of our study show that contact with T. gondii is widespread in minks, and the parasite is common in inland freshwater ecosystems in Germany and Poland. This indicates that watercourses play an important role in the spread of T. gondii oocysts. Full article
(This article belongs to the Special Issue Advances in Parasitic Diseases—Second Edition)
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<p>Sampling areas, sample size (<span class="html-italic">n</span>), and seroprevalence of <span class="html-italic">Toxoplasma gondii</span> in wild American minks (<span class="html-italic">Neogale vison</span>) from Germany and Poland. The orange area represents the geographic distribution of the American mink in Germany and Poland (after Vada et al. [<a href="#B22-pathogens-13-00153" class="html-bibr">22</a>]). Germany: AT Artern (federal state: Thuringia), HB Havelland (Saxony-Anhalt), and TO Torgau (Saxony); Poland: SB Słubice (Lubusz) and PK Pieńsk (Lower Silesian).</p> Full article ">
19 pages, 1037 KiB  
Review
Bacteriophage Challenges in Industrial Processes: A Historical Unveiling and Future Outlook
by Bartosz Kamiński and Jan Paczesny
Pathogens 2024, 13(2), 152; https://doi.org/10.3390/pathogens13020152 - 7 Feb 2024
Viewed by 2194
Abstract
Humans have used fermentation processes since the Neolithic period, mainly to produce beverages. The turning point occurred in the 1850s, when Louis Pasteur discovered that fermentation resulted from the metabolism of living microorganisms. This discovery led to the fast development of fermented food [...] Read more.
Humans have used fermentation processes since the Neolithic period, mainly to produce beverages. The turning point occurred in the 1850s, when Louis Pasteur discovered that fermentation resulted from the metabolism of living microorganisms. This discovery led to the fast development of fermented food production. The importance of industrial processes based on fermentation significantly increased. Many branches of industry rely on the metabolisms of bacteria, for example, the dairy industry (cheese, milk, yogurts), pharmaceutical processes (insulin, vaccines, antibiotics), or the production of chemicals (acetone, butanol, acetic acid). These are the mass production processes involving a large financial outlay. That is why it is essential to minimize threats to production. One major threat affecting bacteria-based processes is bacteriophage infections, causing substantial economic losses. The first reported phage infections appeared in the 1930s, and companies still struggle to fight against phages. This review shows the cases of phage infections in industry and the most common methods used to prevent phage infections. Full article
(This article belongs to the Section Viral Pathogens)
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<p>Changes in the number of species of viruses in each report of ICTV.</p> Full article ">Figure 2
<p>Differences in the morphology of chosen families of phages.</p> Full article ">Figure 3
<p>Branches of food industries using fermentation processes and examples of particular products from each [<a href="#B15-pathogens-13-00152" class="html-bibr">15</a>], along with the timeline of usage fermentation process since pre-Neolithic [<a href="#B13-pathogens-13-00152" class="html-bibr">13</a>,<a href="#B16-pathogens-13-00152" class="html-bibr">16</a>,<a href="#B17-pathogens-13-00152" class="html-bibr">17</a>,<a href="#B18-pathogens-13-00152" class="html-bibr">18</a>,<a href="#B19-pathogens-13-00152" class="html-bibr">19</a>,<a href="#B20-pathogens-13-00152" class="html-bibr">20</a>].</p> Full article ">
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